Miracle-dz/UniFAR-FTUs huggingface dataset:
The effect of an unsteady flow incident on an array of circular cylinders

In this paper we investigate the effect of an inhomogeneous and unsteady velocity field incident on an array of rigid circular cylinders arranged within a circular perimeter (diameter $D_{G}$ ) of varying solid fraction $\unicode[STIX]{x1D719}$ , where the unsteady flow is generated by placing a cylinder (diameter $D_{G}$ ) upwind of the array. Unsteady two-dimensional viscous simulations at a moderate Reynolds number ( $Re=2100$ ) and also, as a means of extrapolating to a flow with a very high Reynolds number, inviscid rapid distortion theory (RDT) calculations were carried out. These novel RDT calculations required the circulation around each cylinder to be zero which was enforced using an iterative method. The two main differences which were highlighted was that the RDT calculations indicated that the tangential velocity component is amplified, both, at the front and sides of the array. For the unsteady viscous simulations this result did not occur as the two-dimensional vortices (of similar size to the array) are deflected away from the boundary and do not penetrate into the boundary layer. Secondly, the amplification is greater for the RDT calculations as for the unsteady finite Reynolds number calculations. For the two highest solid fraction arrays, the mean flow field has two recirculation regions in the near wake of the array, with closed streamlines that penetrate into the array which will have important implications for scalar transport. The increased bleed through the array at the lower solid fraction results in this recirculation region being displaced further downstream. The effect of inviscid blocking and viscous drag on the upstream streamwise velocity and strain field is investigated as it directly influences the ability of the large coherent structures to penetrate into the array and the subsequent forces exerted on the cylinders in the array. The average total force on the array was found to increase monotonically with increasing solid fraction. For high solid fraction $\unicode[STIX]{x1D719}$ , although the fluctuating forces on the individual cylinders is lower than for low $\unicode[STIX]{x1D719}$ , these forces are more correlated due to the proximity of the cylinders. The result is that for mid to high solid fraction arrays the fluctuating force on the array is insensitive to $\unicode[STIX]{x1D719}$ . For low $\unicode[STIX]{x1D719}$ , where the interaction of the cylinders is weak, the force statistics on the individual cylinders can be accurately estimated from the local slip velocity that occurs if the cylinders were removed.
Professional Meta Search Engine Results Ranking Algorithm Based on Genetic Algorithm

Aiming at the problems of meta search engine such as precision,this paper analyzes professional search engine returns results professional correlation in-depth exploration of a given Web page based on genetic algorithm sorting algorithm.In mining to return to the results of independent search engine,in addition to location information of the other information based on the use of genetic algorithm to build a professional Web site correlation model for Web pages related to the degree of professional computing.The algorithm discusses the implementation of the principle and provides programs to improve the algorithm.Experimental results show that the algorithm is effective.
Models of Construction Process Information

Computer-integrated construction (CIC) and concurrent engineering for architecture, engineering, and construction (AEC) require data standards or common information models through which computer systems can exchange project information. High-level conceptual core models are required as unifying references for the more detailed, application-specific models used for the actual information exchange. A variety of core models have been developed in the area of AEC process information. This paper introduces several such models from a variety of projects. It discusses general modeling mechanisms and looks at several issues relating specifically to process modeling for AEC, comparing the approaches of the various core models described, and providing some recommendations. The overall objective is the eventual emergence of generally accepted standards in this area.
On the monotone and primal-dual active set schemes for $\ell^p$-type problems, $p \in (0,1]$

Nonsmooth nonconvex optimization problems involving the $\ell^p$ quasi-norm, $p \in (0, 1]$, of a linear map are considered. A monotonically convergent scheme for a regularized version of the original problem is developed and necessary optimality conditions for the original problem in the form of a complementary system amenable for computation are given. Then an algorithm for solving the above mentioned necessary optimality conditions is proposed. It is based on a combination of the monotone scheme and a primal-dual active set strategy. The performance of the two algorithms is studied by means of a series of numerical tests in different cases, including optimal control problems, fracture mechanics and microscopy image reconstruction.
A Test of the Equivalence Principle using a Long-Period Torsion Balance

This chapter will discuss the Equivalence Principle and motivate experiments testing its validity. The equivalence principle is introduced be providing historical context on its conception and evolution over time. Next, we discuss the fundamental role of the equivalence principle in modern physics and why it requires further experimental validation. This chapter concludes with a discussion of past and future experimental tests of the equivalence principle.
Distributed Networks : Intelligence, Security, and Applications

For many civilian, security, and military applications, distributed and networked coordination offers a more promising alternative to centralized command and control in terms of scalability, flexibility, and robustness. It also introduces its own challenges. Distributed Networks: Intelligence, Security, and Applications brings together scientific research in distributed network intelligence, security, and novel applications. The book presents recent trends and advances in the theory and applications of network intelligence and helps you understand how to successfully incorporate them into distributed systems and services.
A New Name-Based Sampling Method for Migrants Using N-Grams

The set of best methods for sampling migrant populations includes name-based sampling. So far this is done using either ad-hoc lists or onomastic dictionaries for the classification of names. This paper proposes a new name-based procedure, which uses a Bayes-classifier for the n-grams of the name. The new procedure is fault-tolerant of alternate spellings, and also allows the classification of names that are not found in dictionaries. It was tested using the names of about 1.600 foreigners in the PASS panel. Finally, a CATI survey based on the new method in Hesse is described.
Measurements and Analysis of Fingerprinting Structures for WLAN Localization Systems

Channel‐based radio‐frequency fingerprinting such as a channel impulse response (CIR), channel transfer function (CTF), and frequency coherence function (FCF) have been recently proposed to improve the accuracy at the physical layer; however, their empirical performance, advantages, and limitations have not been well reported. This paper provides a comprehensive empirical performance evaluation of RF location fingerprinting, focusing on a comparison of received‐signal strength, CIR‐, CTF‐, and FCF‐based fingerprinting using the weighted k‐nearest neighbor pattern recognition technique. Frequency domain channel measurements in the IEEE 802.11 band taken on a university campus were used to evaluate the accuracy of the fingerprinting types and their robustness to human‐induced motion perturbations of the channel. The localization performance was analyzed, and the results are described using the spatial and temporal radio propagation characteristics. In particular, we introduce the coherence region to explain the spatial properties and investigate the impact of the Doppler spread in time‐varying channels on the time coherence of RF fingerprint structures.
Applying deep learning to scene sketch recognition and 3D sketch-based 3D model retrieval

Human’s sketch understanding is an important and challenging research problem. It has many applications in human computer interaction, multimedia, and computer vision. Most previous methods focus on single-object sketch recognition. Human’s scene sketch understanding has not been studied. In this work, we make the first attempt to tackle this problem. We create the first scene sketch dataset “Scene250” and explore deep learning scheme for scene sketch understanding. We propose a deep Convolutional Neural Network (CNN) model “Scene-Net” and build a novel scene sketch recognition system based on this model. Our system has been tested on the collected scene sketch dataset and compared with other state-of-the-art CNNs and sketch recognition approaches. We also extend our work to sketch-based 3D model retrieval and design a complete retrieval system (CNN-SBR) based on deep CNN. It also achieves better performance than other comparison systems. The experimental results demonstrate the effectiveness and potential of our method.
A New Method for the Off-Line Recognition of Handwritten Digits Based on Convex-Concave Coding

Traditional methods for the off-line recognition of hand-written digits based on skeleton coding have such defects as low speed,huge computation,and so on.The paper proposes a new method based on convex-concave-coding,which only finds the circle and convex areas from the value-associated background,and then combines and codes them.It needs no thinning,which reduces the possibility of errors and rejections because of the thinning distortion,and it needs no complex skeleton tracing and curve fitting,which means it is simple and fast.Experiments show that it can improve the recognition rate and speed rapidly.
Multiple Solutions for an Equation of Kirchhoff Type: Theoretical and Numerical Aspects

A nonlinear boundary value problem related to an equation of Kirchhoff type is considered. The existence of multiple positive solutions is proved through Avery-Peterson Fixed Point Theorem. A numerical method based on Levenberg-Marquadt algorithm combined with a heuristic process is present in order to align numerical and theoretical aspects.
Content-based sports video analysis and composition

This thesis proposes solutions for content-based sports video analysis, including multimodal feature extraction, middle-level representation and semantic event detection. In addition, solutions for sports video composition and personalization are also examined. The first part of the thesis describes our methodology to detect semantic events and event boundaries from both broadcast sports video and non-broadcast sports video. Specifically, to process broadcast sports video, our approach not only uses visual/audio features, we also analyze the web-casting text information associated with the video and synchronize it with the visual/audio features to detect event, locate event boundaries and identify involved players/teams; To process non-broadcast sports video, we select the raw unedited main-camera soccer video as the input and use visual, audio and motion features extraction with multi-level modeling to detect event and event boundaries. Our proposed techniques are evaluated using large sports video data set and achieved satisfactory user acceptance score. The second part of the thesis introduces three novel applications based on our proposed sports video analysis techniques. The first application is a live sports highlight generation system which can automatically detect multiple events from a live sports game and extract a suitable video segment for each event to provide live and personalized game viewership via various mediums. The second application attempts to automatically generate broadcast soccer video composition from multiple raw video captures by detecting events from unedited soccer video and mimicking human director’s practice to control the replay insertion and camera view switching operations. The third application is a personalized music sports video generation system to automatically select and align desired sports video scenes with music clips to generate music video clips. The three proposed systems are tested using objective evaluations and subjective user studies. i ATTENTION: The Singapore Copyright Act applies to the use of this document. Nanyang Technological University Library
WEKO: A New Repository System as a Function of Content Management System

Introduction Content management systems (CMS) such as Drupal, Joomla, and Plone enable users to construct web communities that make available many useful functionalities to their users. In most CMS systems, website functionalities are embodied as modules separate from the core system and installed as the need arises. The National Institute of Informatics in Japan has developed an AJAX-oriented CMS called NetCommons (NC) which is being used by educators. This study proposes a repository module for NC. The name “WEKO” comes from Swahili and means “repository” in that language.
Invariant weighted algebras $L_p^w(G)$

The paper deals with weighted spaces $L_p^w(G)$ on a locally compact group G. If w is a positive measurable function on G then we define the space $L_p^w(G)$, $p\ge1$, as $L_p^w(G)=\{f:fw\in L_p(G)\}$. We consider weights such that these weighted spaces are algebras with respect to usual convolution. It is shown that for p>1 such weights exists on any sigma-compact group. We prove also a criterion known earlier in special cases: $L_1^w(G)$ is an algebra if and only if w is submultiplicative. It is proved that invariant algebras $L_p^w(G)$, $p>1$, have approximate units of standard form, but this may not be true for a non-invariant algebra.
Additive Nonparametric Models with Time Variable and Both Stationary and Nonstationary Regressors

This paper considers nonparametric additive models that have a deterministic time trend and both stationary and integrated variables as components. The diverse nature of the regressors caters for applications in a variety of settings. In addition, we extend the analysis to allow the stationary regressor to be instead locally stationary, and we allow the models to include a linear form of the integrated variable. Heteroscedasticity is allowed for in all models. We propose an estimation strategy based on orthogonal series expansion that takes account of the different type of stationarity/nonstationarity possessed by each covariate. We establish pointwise asymptotic distribution theory jointly for all estimators of unknown functions and also show the conventional optimal convergence rates jointly in the L2 sense. In spite of the entanglement of different kinds of regressors, we can separate out the distribution theory for each estimator. We provide Monte Carlo simulations that establish the favourable properties of our procedures in moderate sized samples. Finally, we apply our techniques to the study of a pairs trading strategy.
Improved CamShift Algorithm for Face Tracking

Considered classic CamShift algorithm used for face tracking when there being large color regions in the scene easily leading to inaccurate tracking,an improved CamShift algorithm integrating the template matching algorithm is proposed.Making the template matching successing or not in color probability distribution as iteration termination condition of CamShift algorithm can well figure out the trouble caused by color regions in face tracking.Experimental results prove the validity of the method.
Discussion of "Statistical modelling of citation exchange between statistics journals" by Varin, Cattelan and Firth

With the recent advances in text analysis, I believe we have the technology to analyse the ‘quality’ (‘weight’, ‘temperature’) of citations, as opposed to their mere number. For example, arguably, the citation in “other recent contributions include Anon (2015)” carries less weight, or has ‘lower temperature’ than that in “this work is motivated by Anon (2015)”. In the same vein, a citation to a paper made once in a manuscript may be ‘less hot’ than a citation to another paper made twice.
Shifted Chebyshev schemes for solving fractional optimal control problems

Two schemes to find approximated solutions of optimal control problems of fractional order (FOCPs) are investigated. Integration and differentiation matrices were used in these schemes. These schemes used Chebyshev polynomials in the shifted case as a functional approximation. The target of the presented schemes is to convert such problems to optimization problems (OPs). Numerical examples are included, showing the strength of the schemes.
Forecasting the 8 May 2017 Severe Hail Storm in Denver, Colorado, at a Convection-Allowing Resolution: Understanding Rimed Ice Treatments in Multimoment Microphysics Schemes and Their Effects on Hail Size Forecasts

Day-ahead (20–22 h) 3-km grid spacing convection-allowing model forecasts are performed for a severe hail event that occurred in Denver, Colorado, on 8 May 2017 using six different multimoment microphysics (MP) schemes including: the Milbrandt–Yau double-moment (MY2), Thompson (THO), NSSL double-moment (NSSL), Morrison double-moment graupel (MOR-G) and hail (MOR-H), and Predicted Particle Properties (P3) schemes. Hail size forecasts diagnosed using the Thompson hail algorithm and storm surrogates predict hail coverage. For this case hail forecasts predict the coverage of hail with a high level of skill but underpredict hail size. The storm surrogate updraft helicity predicts the coverage of severe hail with the most skill for this case. Model data are analyzed to assess the effects of microphysical treatments related to rimed ice. THO uses diagnostic equations to increase the size of graupel within the hail core. MOR-G and MOR-H predict small rimed ice aloft; excessive size sorting and increased fall speeds cause MOR-H to predict more and larger surface hail than MOR-G. The MY2 and NSSL schemes predict large, dense rimed ice particles because both schemes predict separate hail and graupel categories. The NSSL scheme predicts relatively little hail for this case; however, the hail size forecast qualitatively improves when the maximum size of both hail and graupel is considered. The single ice category P3 scheme only predicts dense hail near the surface while above the melting layer large concentrations of low-density ice dominate.
Towards Developing an Effective Hand Gesture Recognition System for Human Computer Interaction: A Literature Survey

Gesture recognition is a mathematical analysis of movement of body parts (hand / face) done with the help of computing device. It helps computers to understand human body language and build a more powerful link between humans and machines. Many research works are developed in the field of hand gesture recognition. Each works have achieved different recognition accuracies with different hand gesture datasets, however most of the firms are having insufficient insight to develop necessary achievements to meet their development in real time datasets. Under such circumstances, it is very essential to have a complete knowledge of recognition methods of hand gesture recognition, its strength and weakness and the development criteria as well. Lots of reports declare its work to be better but a complete relative analysis is lacking in these works. In this paper, we provide a study of representative techniques for hand gesture recognition, recognition methods and also presented a brief introduction about hand gesture recognition. The main objective of this work is to highlight the position of various recognition techniqueswhich can indirectly help in developing new techniques for solving the issues in the hand gesture recognition systems. Moreover we present a concise description about the hand gesture recognition systems recognition methods and the instructions for future research.
The Current Situation and Future of Seismic Data Prestack Noise Attenuation Techniques

Seismic data prestack noise attenuation is one of the key problems of seismic data processing. However, this problem has not been well solved so far and becomes a barrier of enhancing the resolution of seismic data. Meanwhile, how to efficiently eliminate multiples generated by the multi reflections between subsurface interfaces is the major problem of seismic data prestack noise attenuation. So far, many efforts have been made for the purpose of better attenuating multiples. This paper summarizes some popular and efficient techniques in industry including Radon transform, F K method and Beamforming for multiple attenuation, predictive deconvolution for eliminating water reverberation and K L transform for random noise attenuation.
Abstracting Linear Programs with Arrays into Linear Programs

We introduce a counterexample guided abstraction and refinement procedure for linear programs with arrays. Our procedure starts by abstracting away all array elements from the initial program and then it incrementally refines the abstract program by including array elements as suggested by the refinement process. While, in the worst case, the procedure may lead to the generation and analysis of the abstract program obtained by considering all the array elements of the concrete program, in many cases of interests only a few array elements suce to successfully conclude the analysis. This is unlike other approaches in which the complexity of the analysis always increases with the size of the arrays involved in the input program. Moreover our analysis of arrays is precise, unlike other approaches that trade precision for eciency and therefore may return false negatives.
Understanding Affect in Images

Jana Machajdik Institute of Computer Aided Automation, Vienna University of Technology Favoritenstraße 9/183, 1040 Vienna, Austria jana@caa.tuwien. ac.at Allan Hanbury Information Retrieval Facility Tech Gate Vienna, Donau City Straße 1, 1220 Vienna, Austria a.hanbury@ir-facility.org Julian Stöttinger Institute of Computer Aided Automation, Vienna University of Technology Favoritenstraße 9/183, 1040 Vienna, Austria julian@caa.tuwien. ac.at
Almost conformal Ricci solitons on 3-dimensional trans-Sasakian manifold

In this paper we have shown that if a $3$-dimensional trans-Sasakian manifold M admits conformal Ricci soliton $(g,V,\lambda )$ and if the vector field $V$ is point wise collinear with the unit vector field $\xi$, then $V$ is a constant multiple of $\xi$. Similarly we have proved that under the same condition an almost conformal Ricci soliton becomes conformal Ricci soliton. We have also shown that if a $3$-dimensional trans-Sasakian manifold admits conformal gradient shrinking Ricci soliton, then the manifold is an Einstein manifold.
Removing Raindrops in Continuous Video Images for Fixed-Object Surveillance Systems

In this paper, a dynamic algorithm is proposed that is aimed at removing raindrops within fixed background video images according to the volume of raindrops. In surveillance videos with fixed backgrounds, when the field of vision is obstructed because of falling rain or snow, obtaining picture information on the objects becomes difficult. Therefore, obstacles such as raindrops that obstruct the field of vision should be removed from pictures to obtain more specific picture information. The proposed technique obtains images on a periodical basis from a fixed background picture and assesses whether there are raindrops in the present screen among the obtained images. The proposed technique predicts the volume of raindrops by comparing images obtained periodically and removes raindrops by applying a different dynamic algorithm based on the predicted volume of raindrops. This study embodied and experimented with the proposed technique and verified that the result was excellent.