Miracle-dz/UniFAR-FTUs huggingface dataset:
Electronic documents give reproducible research a new meaning: 62nd Ann

A revolution in education and technology transfer follows from the marriage of word processing and software command scripts. In this marriage an a.uthor attaches to every figure caption a pushbutton or a name tag usable t,o recalculate the figure from all its data, parameters, and programs. This provides a concrete definition of reproducibility in computationally oriented research. Experience at the Stanford Exploration Project shows that preparing such electronic documents is lit,tle effort beyond our customary report writing; mainly, we need to file everything in a systematic way.
Automatic system for making web content accessible for visually impaired users

Although visually impaired people can access digital information by using computers, usually the content of Internet pages is not fully accessible. The dissemination of information available through the World Wide Web makes universal access more and more important and supports visually impaired people in their everyday life. In this paper we present a new system which serves visually impaired people for browsing and interacting with web pages. We propose a system, which uses translation rules to render web pages upon user requests.
Applications of the GLMSELECT Procedure for Megamodel Selection

When you can select regression models from tens of thousands of effects, what possibilities for modeling are open to you? This paper explores applications of the GLMSELECT procedure in SAS/STAT ® software to such problems. The GLMSELECT procedure supports a variety of model selection methods for general linear models. Examples of megamodels arising in genomic data analysis and nonparametric modeling are discussed. In addressing these examples, built-in facilities of the procedure to handle validation and test data are highlighted in addition to techniques for extending the procedure’s functionality to address model selection bias by using bootstrap-based model averaging.
A Standard Input Format for Multiperiod Stochastic Linear Programs

Data conventions for the automatic input of multiperiod stochastic linear programs are described. The input format is based on the MPSX standard and is designed to promote the efficient conversion of originally deterministic problems by introducing stochastic variants in separate files. A flexible "header" syntax generates a useful variety of stochastic dependencies. An extension using the NETGEN format is proposed for stochastic network programs.
The Automatic Generation Of Software Test Data Sets Using Adaptive Search Techniques

Test sets which cover all branches of a library of five procedures which solve the triangle problem, have been produced automatically using genetic algorithms. The tests are derived from both the structure of the software and its formal specification in Z. In a wider context, more complex procedures such as a binary search and a generic quicksort have also been tested automatically from the structure of the software. The value of genetic algorithms lies in their ability to handle input data which may be of a complex data structure, and to execute branches whose predicate may be a complicated and unknown function of the input data. A disadvantage of genetic algorithms may be the computational effort required to reach a solution.
Maliyet Bilgileri Temeline Dayalı Pazarlama Kararları İçin Pazarlama Muhasebesi

OZET Gelecekteki faaliyetlerin planlanmasi ve kontrolunde i sletmenin muhasebe bolumunden saglanan bilgilere duyulan gereksinim genis kabul gormektedir. Maliyet muhasebesi pazarlamada karar vermeye yonelik bir model olarak kullanilmaktadir. Pazarlamayla ilgili saglikli karar alabilmek icin, maliyet muhasebesince saglanacak bilgilere gereksinim vardir. Bu anlamda maliyet muhasebesi, pazarlama, satis ve dagitimla ilgili kararlarin sa glam temellere dayandirilmasina yonelik bir arac olarak kullanilir. Pazarlama muhasebesi, pazarlamayla ilgili bilgilerin toplanmasi, calisanlara iletilmesi, pa- zarlama, satis ve dagitim maliyetlerinin hesaplanmasinda kullanilmaktadir ve musteri yarari, marka- nin olusturulmasi, degerinin artirilmasi ve korunmasi, rekabete yonelik fiyatlama gibi konularla ilgi- lenir.
On the Importance of Scalability : Should k-NN Genre Classification be Revisited?

Personal or professional music collections grow at a very fast pace due to the ease with which digital music can be created, shared, stored and manipulated. As a result, modern music management and browsing require the use of searchable metadata built on low-level features describing the contents of songs, in addition to titles, artists or album names. Musical genre is an example of such metadata, which has been shown to be useful. Currently, the best approaches for automatic genre classification achieve high quality results, with around 91% classification accuracy. These approaches, however, use sophisticated classification algorithms (that are hence quite slow) evaluated on standard music collections (that are small). Using such approaches in the real world, where collections are orders of magnitude larger, is therefore difficult in practice. In contrast, this report addresses large scale genre classification based on a k-nearest neighbor paradigm. The rationale for using such a simple approach is that it is much faster than all other state-of-the-art schemes, which is required to cope with scale. In the past, the quality of k-NN classification has been deemed insufficient in the literature. We claim, however, that the ability of k-NN schemes to gracefully cope with scale is a strong motivation for working to improve their accuracy. As a first step in this direction, this report shows, through a number of experiments, that k-NN classification can indeed yield quite good results for automatic genre classification. Furthermore, the classification times that we report show that k-NN classification is very fast, which is necessary for real life collections.
Affective Interaction with an Expressive Robot

In our research, we introduce Socially Interactive Robot Eva which has the capability of doing human-like emotions and facial expressions (Fig1). Our research on affective modeling and facial animation on the robotic face is applied for a museum guide robot in the European research project INDIGO [1] There are three primary components in this research: , test it on virtual characters and then transfer it to the robotic character. Fig4 shows the interaction architecture integrating different software components.
A pattern for separating assembly and processing

Using a pattern such as Builder [Design], which constructs objects from a generic data stream based on the content in the stream, will decouple the interfaces between different development groups, by insulating the operations team from knowing the definition of units of work, and the details of which packets belong in which collections. It is still necessary to decouple the upstream and downstream components.
Wireless LANs: Implementing High Performance IEEE 802.11 Networks

From the Publisher: This book provides the following benefits to readers: Ability to select the most effective wireless LAN type from a wide assortment of recent and emerging standards. Independent assessment of competing wireless LAN technologies. More efficient design and operational support of wireless LANs because of an understanding of wireless LAN protocol operations and frame structures. Definition of typical requirements and technology assessment parameters, providing a basis for evaluating wireless LANs. Vision of the future of wireless LANs. Real-world experiences through case studies and implementation tips located throughout the book. Quick overview of the features, pros, and cons of each of the wireless LAN standards located at the beginning of each chapter.
L’impact des pratiques de Supply Chain Management sur la performance de l’entreprise

(VF)S’il existe de nombreuses etudes reliant le Supply Chain Management (SCM) et le developpement d’un avantage concurrentiel, elles restent neanmoins a la fois dispersees et incompletes. Cet article vise tout d’abord a expliciter la notion de pratiques de SCM (PSCM) puis a identifier l’impact de ces pratiques sur la performance. Au final, le modele teste l’influence de 3 PSCM sur 8 dimensions complementaires (financieres et non financieres) de la performance de la firme dans le contexte francais. Nos resultats, obtenus par le biais d’une serie d’equations de regression, montrent une influence differenciee des PSCM sur la performance, tant en termes de types de pratiques discriminantes qu’en termes de types d’indicateurs de performance influences. (VA)Numerous studies examine the relationship between Supply Chain Management (SCM) and the development of a competitive advantage. These studies, however, are mostly both incomplete and disparate. The purpose of this article is to identify the precise nature of SCM practices and to empirically test the relationship between the latter and performance. More specifically, this article tests the impact of 3 SCM practices on 8 different performance metrics, both financial and non financial. Our results show that SCM practices determine performance in different ways and at different levels, both considering the type of practice and the type of performance indicator used.
Segmentation based approach for Image Categorization

Increasing use of electronic devices make enormous amount of multimedia data (e.g. Images, video, audio, time series, spatial and spatio-temporal) dataset. Now documents are also available in the form of images. Document based image classification is one of the challenging task of image processing. It is more challenging when the document is containing maximum similarity in all the classes. In present paper we have used the real data of Chhattisgarh Pharmacy council that initially worked on manual system and managed all the medicals, pharmacist data manually. Council issued a certificate to each pharmacy as a licence. The main focus of this paper is to device an efficient algorithm which categorized all classes of images document separately using segment of original image. Secondary, Each image document have an unique registration number. The objective is to recognize the registration number that is set of character written in the certificate and store it into database for further query processing purpose. Many methods for image classification has been applied like, Histogram based, spatiogram comparisons, template based matching, LLC based classification. None of the classifiers accuracy was more than 67%. The challenge is extraction of discriminating features, that categorized the images efficiently. In proposed paper we have used segmentation based algorithm in order to extract accurate features and hybrid algorithm that is able to classify the images and recognize the registration number (set of characters) of the certificates. The hybrid algorithm gives better result than other classifier its accuracy was 82.72005152%.
Compendium of Parameterized Problems

This document includes a list of computational problems that have been studied within the framework of parameterized complexity [81]. It is mainly based on “A Compendium of Parameterized Complexity Results”, version 2.0 (May 22, 1996), by Michael T. Hallett and H. Todd Wareham, and on Downey and Fellows’ book [81]. It includes, however, several new results that have been published in the last few years. Every computational problem in this document has one or more parameterized versions. Currently there are 312 computational problems listed in alphabetical order. For each of them we report the known parameterized versions (for a grand total of 376), the corresponding parameterized complexity results, and the references to the relevant articles in the bibliography. This document does not pretend, of course, to be complete; for instance, it does not consider computational problems that are not decision problems. Moreover, this document likely includes errors and omissions. If you have corrections, suggestions, new or missing results, please send them to compendium@sprg.uniroma2. it.
Durabilité des Bétons Auto-Plaçants

Les betons autoplacants (BAP) sont des betons tres fluides dont la mise en place sans vibration presente plusieurs avantages tant au niveau environnemental, humain, technologique qu'economique qui interessent de plus en plus les industriels. Cependant, une question reste souvent posee : a resistance mecanique egale, le beton autoplacant est-il aussi durable que le beton vibre traditionnellement employe jusqu'alors ? L'objectif de ce projet de recherche a ete de donner une reponse claire a ce probleme. Pour cela, differents BAP et betons vibres (BV) de resistance mecanique equivalente ont ete coules avec les memes constituants, un squelette granulaire identique (a l'exception des betons a hautes performances) et dans une gamme de resistance allant de 20 a 60 MPa. Les principales differences entre les deux types de beton sont le volume de pâte et le dosage en superplastifiant plus important pour les BAP et l'emploi eventuel d'un agent de viscosite dans ces derniers. Les resultats des essais experimentaux menes sur ces formulations dans les domaines mecanique et physico-chimique ont montre qu'il y avait tres peu de differences entre les deux types de beton. Le fluage des BAP semble legerement superieur a celui des BV, tandis que les autres proprietes mecaniques (module d'elasticite, retrait) et de transfert (permeabilite a l'oxygene, diffusion des ions chlore, absorption capillaire, carbonatation et lessivage au nitrate d'ammonium) peuvent etre considerees comme equivalentes entre les BAP et les BV.
Policy supervised exact state reconstruction in real-time embedded control systems

In case of computer control systems which require application of optimal control algorithms, it is required to have immediate access to state variables of the controlled system. When these state variables are unavailable or cannot be measured, it is necessary to use state observers that the reconstruct required system state based on extrapolation of the system input and output signals. However, the latest trends in control systems applications express additional requirements regarding increased flexibility and ability to adjust to changing environment conditions. This results in a combination of classic control algorithms with various modern techniques of supervision and control which leads to design of hierarchical multilayer computer control systems. In some cases, depending on deployment environment, there may appear some constraints or additional requirements to be satisfied, which may reduce the range of possible solutions. This applies especially to embedded systems, where resource constraints are always an issue which has to be taken into account. This paper presents a new architecture for control systems with hierarchical exact state observers. The architecture incorporates policy-based computing to facilitate flexible, recon-figurable supervision logic and the achievement of environment awareness.
Automatic Readability Assessment

We describe the development of an automatic tool to assess the readability of text documents. Our readability assessment tool predicts elementary school grade levels of texts with high accuracy. The tool is developed using supervised machine learning techniques on text corpora annotated with grade levels and other indicators of reading difficulty. Various independent variables or features are extracted from texts and used for automatic classification. We systematically explore different feature inventories and evaluate the grade-level prediction of the resulting classifiers. Our evaluation comprises well-known features at various linguistic levels from the existing literature, such as those based on language modeling, part-of-speech, syntactic parse trees, and shallow text properties, including classic readability formulas like the Flesch-Kincaid Grade Level formula. We focus in particular on discourse features, including three novel feature sets based on the density of entities, lexical chains, and coreferential inference, as well as features derived from entity grids. We evaluate and compare these different feature sets in terms of accuracy and mean squared error by cross-validation. Generalization to different corpora or domains is assessed in two ways. First, using two corpora of texts and their manually simplified versions, we evaluate how well our readability assessment tool can discriminate between original and simplified texts. Second, we measure the correlation between grade levels predicted by our tool, expert ratings of text difficulty, and estimated latent difficulty derived from experiments involving adult participants with mild intellectual disabilities. The applications of this work include selection of reading material tailored to varying proficiency levels, ranking of documents by reading difficulty, and automatic document summarization and text simplification.
Augmenting RAID with an SSD for energy relief

In this paper, we describe a design of a novel architecture for RAID that uses an SSD as a large cache to conserve energy. This approach stems from the fact that short term footprints are small enough to be efficiently managed within an SSD. More specifically, in this study, we consider two simple approaches to reduce the energy consumed in RAID. First, when a read happens in RAID, a copy of the read request is copied to the SSD, so that future requests may be serviced by the SSD. Then, for writes, all writes are buffered in SSDs so that the interval between requests may be increased reducing activities at RAID disks. We incorporate these approaches into a real implementation of a RAID 5 system that consists of four hard disks and an SSD in a Linux environment. Our preliminary results in actual performance measurements using the cello99 and SPC traces show that energy consumption is reduced by a maximum of 14%.
Efficient Computation of the Minimum Hausdorff Distance for Visual Recognition

We have developed a method, using the minimum Hausdorff distance, for visually locating an object in an image. This method is very reliable, and fast enough for real-world applications. A visual recognition system takes an image and a model of an object which may occur in that image; these images and models are composed of features (points, line segments, etc.). The system locates instances of the model in the image by determining transformations of the model which bring a large number of model features close to image features. One of the unique strengths of the Hausdorff distance is the reverse distance which reduces the frequency of erroneous matching between a model and a cluttered portion of the image. The Hausdorff distance is a measure defined between two point sets representing a model and an image. Its properties make it attractive for model-based recognition; one of these properties is that the Hausdorff distance is a metric. The minimum Hausdorff distance is used to find a transformation of the model which brings it into closest correspondence with the image. This can be done by searching over a space of allowable transformations. In some cases, the minimum Hausdorff distance is also a metric. The Hausdorff distance can be modified so that it is reliable even when the image contains multiple objects, noise, spurious features, and occlusions. We construct lower bounds which show that finding the exact transformation that minimises the Hausdorff distance may be quite expensive. We develop a rasterised approach to the search and a number of techniques which allow this search to be performed efficiently. The principal search technique used is transformation space subdivision. The space of transformations is searched in a tree-like fashion: a large region is examined as a unit, and if the results of this examination are good, it is subdivided and each of the subregions examined in turn; if the results are not good, then the region is discarded. We discuss some implementations of this approach, together with their applications to practical problems such as motion tracking and mobile robot navigation.
Simulation and Design of Au-tomobile Sunroof Buffeting Noise Control

This paper presents the success story of an application of Computational Fluid Dynamics (CFD) analysis for automotive sunroof buffeting simulation and noise control design. Computational analyses of flow over an open sunroof of a car are performed to study the buffeting phenomenon and to determine the buffeting noise magnitude and frequency. Computations are performed for sunroofs with two types of buffeting noise control mechanisms. Numerical predictions are compared with the wind tunnel measurements. It is shown that CFD analysis has great potential for sunroof design and development
A Statistical MT Tutorial Workbook

We want to automatically analyze existing human sentence translations, with an eye toward building general translation rules — we will use these rules to translate new texts automatically. I know this looks like a thick workbook, but if you take a day to work through it, you will know almost as much about statistical machine translation as anybody! The basic text that this tutorial relies on is Brown et al, “The Mathematics of Statistical Machine Translation”, Computational Linguistics, 1993. On top of this excellent presentation, I can only add some perspective and perhaps some sympathy for the poor reader, who has (after all) done nothing wrong. Important terms are emphasized throughout!
Decompiling with Definite Clause Grammars

Abstract : Decompiling is the process of deriving a computer program in a high level language from one in machine-code or assembly language. Defense applications of decompiling include maintenance of obsolescent equipment, production of scientific and technical intelligence and assessment of systems for hazards to safety or security. This paper describes an approach to the rapid generation of decompilers through the use of Definite Clause Grammars. , a class of abstract grammars which can be executed as prolog programs. The approach is illustrated using toy languages. An environment which permits the integration of diverse sources of knowledge relevant to the decompilation problem and provides a graphical interface is described.
XML Storage Method Based on the Relational Database using Statistics of XML Documents

Many XML storage methods based on relational databases have already been proposed. These conventional stor- age methods, however, increase the number of tables because of a wide variety of structures of XML documents and make the search cost high. Although there are also storage methods using DTD which is a document model, the descriptive power of DTDs is insufficient in some cases. In this paper, an efficient XML storage method without using DTDs is proposed, which generates a schema for few number of tables with little redundancy by some statistics of XML documents. In order to reduce the number of tables, appropriate data types for the characteristic structures are defined. We try to store elements of a few occurrences in the same table. Which elements are stored in the same table is decided by using a function evaluating the
Six Degree-of-Freedom Haptic Display

We present an algorithm for haptic display ofmoderately complex polygonal models with a six degreeof freedom (DOF) force feedback device. We make use ofincremental algorithms for contact determination betweenconvex primitives. The resulting contact information isused for calculating the restoring forces and torques andthereby used to generate a sense of virtual touch. To speedup the computation, our approach exploits a combinationof geometric locality, temporal coherence, and predictivemethods to compute object-object contacts at kHz rates.The algorithm has been implemented and interfaced witha 6-DOF PHANToM Premium 1.5. We demonstrate itsperformance on force display of the mechanical interactionbetween moderately complex geometric structures that canbe decomposed into convex primitives.