Miracle-dz/UniFAR-FTUs huggingface dataset:
Maximize Performance on GPUs Using the Rake-based Optimization: A Case Study

In this paper, we analyze the trade-offs encountered when minimizing the total execution time using the rake-based applications on GPUs. We use clustering data streams as a case study, and present a rake-based implementation for it, making it more efficient in terms of memory usage. In order to maximize performance for different problem sizes and architectures, we propose a model-based auto-tuning solution. Experimental results show that our fully optimized implementation can perform 2.1x and 1.4x faster than the native OpenCL implementation on NVIDIA GTX480 and AMD HD5870, respectively; it can also achieve 1.4x to 3.3x speedup relative to the original CUDA implementation solution on GTX480.
Political Influence on the Central Bank- International Evidence

Political influence on the central bank is measured bere by looking at the probability that a central bank governor will be replaced shortly after a political change of government. The governor changes about half the time witbin six months of a nonconstitutional or other radical change of government-a military coup or a restoration of democracy. The governor is much less likely to change within six months following a routine change in the head of government-about one-fourth of the time in developing countries and one-tenth in industrial countries. These indicators vary across countries and correlate statistically with inflation and its variability and with real growth and real interest rates. Differences in the vulnerability of the central bank to political instability, in political instability itself, and in central bank turnover in nonpolitical periods seem to be a major part of the explanation for why developing countries have, on average, higher and more variable inflation than industrial countries do.
MEASUREMENT AND ANALYSIS OF IP NETWORK TRAFFIC

Traffic measurement and analysis are crucial to the design, operation and maintenance of wide-area networks based on Internet Protocol. This paper has outlined some important issues in real time traffic measurement and analysis. Firstly we give a brief survey on the related work of Internet traffic measurement, and then we focus on the general measurement methodologies. At last we present several visualizing results of our analysis upon some TCP traffic data.
A multi-resolution approach to depth field estimation in dense image arrays

In this paper a multi-resolution depth field estimation algorithm for plenoptic cameras is presented. To face the potential accuracy losses originated from ambiguity problems arising in flat surface regions, still preserving bandwidth in correspondence of edges, a multi-resolution scheme is proposed. The achieved results show that the proposed local optimization method outperforms state of the art more complex global optimization based methods.
The Gravity Model and the Problem of Zero's in Agrifood Trade

and this is a problem when estimating log-linear gravity equations. This has caused many researchers to either ignore the zero trade flows or to replace the zero with a small positive number. Both of these actions bias the resulting parameter estimates of the gravity equation. In this study we correct for this misspecification by using the Heckman selection model to estimate bilateral trade flows for 46 agrifood products, for the period 1990 to 2000, for 52 countries. In our sample, selection bias rarely affects the signs of variables but often has a substantial effect on the magnitude, statistical significance and economic interpretation of the marginal effects. Hence, treating zero trade flows properly is important from both a statistical and an economics perspective.
Specifying Languages and Verifying Programs with K http : / / kframework . org

—K is a rewrite-based executable semantic framework for defining languages. The K framework is designed to allow implementing a variety of generic tools that can be used with any language defined in K, such as parsers, interpreters, symbolic execution engines, semantic debuggers, test-case generators, state-space explorers, model checkers, and even deductive program verifiers. The latter are based on matching logic for expressing static properties, and on reachability logic for expressing dynamic properties. Several large languages have been already defined or are being defined
Provenance, XML, and the Scientific Web

Science is now being revolutionized by the capabilities of distributing computation and human effort over the World Wide Web. This revolution offers dramatic benefits but also poses serious risks due to the fluid nature of digital information. The Web today does not provide adequate repeatability, reliability, accountability and trust guarantees for scientific applications. One important part of this problem is tracking and managing provenance information, or metadata about sources, authorship, derivation, or other historical aspects of data. In this paper, we discuss motivating examples for provenance in science and computer security, introduce four models of provenance for XML queries, and discuss their properties and prospects for further research.
Intangibilidade e inovação em empresas no Brasil

This study aims at investigating the relationship between the degree of intangibility, whose definition is based on accounting information, and the degree of innovation in innovating Brazilian companies, measured by the “Indice Brasil de Inovacao (IBI)” – Brazil Innovation Index – in order to discover the effects of the recognition of intangible assets in these companies’ assets. It is a descriptive research of a qualitative nature achieved through documental analysis. The secondary data – Standardized Financial Demonstrations (SFD) which provides necessary information for calculating the market value (number of shares multiplied by value of each share) in years 2007, 2008, and 2009 – were collected in the BMF (ii) companies in more innovative sectors displayed greater IIAIs, which is evidence that these companies channeled more investment on intangibles when compared to companies in less innovative sectors; (iii) in 2009, the average market value of innovative companies more than doubled its own capital value, and this difference was attributed to their intangibles; and, (iv) based on analysis of the ranking of 10 companies with the highest IDs and 10 companies with the lowest IDs, it is not possible to identify any relation between ID and the degree of innovation in surveyed companies.
Reducing confounding bias in observational studies that use text classification

As text classifiers become increasingly used in observational studies, it is critical to consider not only their accuracy but also their robustness to changes in the data distribution. In this paper, we consider the case where there is a confounding variable Z that influences both the text features W and the class variable Y . For example, a classifier trained to predict the health status of a user based on their online communications may be confounded by socioeconomic variables. When the influence of Z changes from training to testing data, we find that classifier accuracy can degrade rapidly. Our approach, based on Pearl’s back-door adjustment, estimates the underlying effect of a text variable on the class variable while controlling for the confounding variable. We conduct an observational study to estimate the effect of location on dispositional affect, with gender as a confounder. We find that our adjustment results in more accurate estimates of effect sizes over a range of possible confounding strengths.
Lightweight Personal Bindings : User tailored workspaces in multiple display environments

This paper presents a novel interaction technique for Multiple Display Environments (MDEs) called lightweight personal bindings. This technique enables users to easily bind edges from one display to another and move seamlessly between displays. The goal of this work is to support collocated collaboration in a dynamic multi-display environment while accommodating users’ personal preferences. With lightweight personal bindings, each user can choose their own display connections and create a personalized MDE. This approach also helps manage changes in the environment as devices enter, move, or leave.
Towards Collaborative, Dynamic and Complex Systems (Short Paper)

Service orientation has significantly facilitated the development of complex distributed systems spanning multiple organizations. However, different application areas approach such systems in domain-specific ways, focusing on particular aspects relevant only for their application types. As a result, we observe a very fragmented landscape of service-oriented systems, which does not enable collaboration across organizations. To address this concern, in this work we introduce the notion of Collaborative, Dynamic and Complex (CDC) systems and position them with respect to existing technologies. In addition, we present how CDC systems are modeled and the steps to provision and execute them. We also contribute an architecture enabling CDC Systems with full life cycle coverage that allows for leveraging service-oriented and Cloud-related technologies.
Relative Young’s modulus identification using elastography

Some biological tissues like the prostate can be considered as a linear isotropic medium, at least for small strains. An interesting problem - from the medical point of view - is to detect heterogeneities where the Young’s modulus takes a different value from the background. A homogeneous medium is considered here, except in some regions where Young’s modulus takes a different value. A method is proposed to reconstruct an approximation of relative Young’s modulus, that is the ratio of Young’s moduli. The main tool is a general method for inverse problems: it is an implementation of Gauss-Newton’s method that uses few memory and few computations, based on the use of direct and adjoint derivative. This method is illustrated with experimental results on a gelatin phantom: the regularization property of Gauss-Newton’s algorithm allows to locate the larger heterogeneities.
NONLINEAR IDENTIFICATION AND CONTROL OF DC-DC CONVERTER BASED ON HETEROGENEOUS APPROACH

In this paper, the philosophy of the heterogeneous control combined with landmark description is applied for controlling dc-dc converters. In our approach, there are combined fuzzy logic approach with some crisp information regarding the system evolution, the so called landmark based representation. On this structure seven behavioural items are defined, allowing delimiting the so called fundamental functioning regions in the state space of the converter. The necessary and sufficient conditions for steady state evolution are determined. The qualitative properties of these regions are established and a nonlinear heterogeneous controller is designed. Experimental results are presented pointing out the advantages of the proposed method.
A Nonconservative LMI Condition for Stability of Switched Systems With Guaranteed Dwell Time

Ensuring stability of switched linear systems with a guaranteed dwell time is an important problem in control systems. Several methods have been proposed in the literature to address this problem, but unfortunately they provide sufficient conditions only. This technical note proposes the use of homogeneous polynomial Lyapunov functions in the non-restrictive case where all the subsystems are Hurwitz, showing that a sufficient condition can be provided in terms of an LMI feasibility test by exploiting a key representation of polynomials. Several properties are proved for this condition, in particular that it is also necessary for a sufficiently large degree of these functions. As a result, the proposed condition provides a sequence of upper bounds of the minimum dwell time that approximate it arbitrarily well. Some examples illustrate the proposed approach.
Real-time PCR determination of IMPDH1 and IMPDH2 expression in blood cells.

BACKGROUND Inosine monophosphate dehydrogenase (IMPDH) catalyzes the rate-limiting step in de novo guanine nucleotide synthesis and is implicated in cell cycle control. Inhibition of this enzyme is associated with immunosuppressive, antiviral, and antitumor activity. IMPDH basal activity increases after initiation of immunosuppressive therapy. METHODS A real-time reverse-transcription PCR assay was developed and validated for mRNA quantification of the 2 human IMPDH isoforms. Target gene expressions were normalized to the geometric mean of 3 housekeeping genes. Assay utility was tested by analyzing patient samples and cultured cells exposed to immunosuppressive drugs such as the IMPDH inhibitor mycophenolic acid. RESULTS The assay was linear over 6 logs of cDNA input and demonstrated specific quantification of IMPDH1 and IMPDH2 expression in cultured cells and patient samples. Limits of detection and quantification were 10 and 10(3) copies of cDNA per reaction, respectively. Within-run and total between-day CVs were <15% for normalized expression. Changes in IMPDH1 and 2 expression were observed in patient samples after initiation of an immunosuppressive regimen that included calcineurin inhibitors, mycophenolate mofetil, and steroids. CONCLUSIONS This assay can be used to study the regulation of IMPDH expression and the involvement of the enzymes in immunological and malignant proliferative conditions. This may contribute to the processes of drug development and to the establishment of monitoring strategies for treatment effect and disease activity.
Detection of malignant mesothelioma using nuclear structure of mesothelial cells in effusion cytology specimens

Mesothelioma is a form of cancer generally caused from previous exposure to asbestos. Although it was considered a rare neoplasm in the past, its incidence is increasing worldwide due to extensive use of asbestos. In the current practice of medicine, the gold standard for diagnosing mesothelioma is through a pleural biopsy with subsequent histologic examination of the tissue. The diagnostic tissue should demonstrate the invasion by the tumor and is obtained through thoracoscopy or open thoracotomy, both being highly invasive surgical operations. On the other hand, thoracocentesis, which is removal of effusion fluid from the pleural space, is a far less invasive procedure that can provide material for cytological examination. In this study, we aim at detecting and classifying malignant mesothelioma based on the nuclear chromatin distribution from digital images of mesothelial cells in effusion cytology specimens. Accordingly, a computerized method is developed to determine whether a set of nuclei belonging to a patient is benign or malignant. The quantification of chromatin distribution is performed by using the optimal transport‐based linear embedding for segmented nuclei in combination with the modified Fisher discriminant analysis. Classification is then performed through a k‐nearest neighborhood approach and a basic voting strategy. Our experiments on 34 different human cases result in 100% accurate predictions computed with blind cross validation. Experimental comparisons also show that the new method can significantly outperform standard numerical feature‐type methods in terms of agreement with the clinical diagnosis gold standard. According to our results, we conclude that nuclear structure of mesothelial cells alone may contain enough information to separate malignant mesothelioma from benign mesothelial proliferations. © 2015 International Society for Advancement of Cytometry
Composite Kernel Local Angular Discriminant Analysis for Multi-Sensor Geospatial Image Analysis

With the emergence of passive and active optical sensors available for geospatial imaging, information fusion across sensors is becoming ever more important. An important aspect of single (or multiple) sensor geospatial image analysis is feature extraction - the process of finding "optimal" lower dimensional subspaces that adequately characterize class-specific information for subsequent analysis tasks, such as classification, change and anomaly detection etc. In recent work, we proposed and developed an angle-based discriminant analysis approach that projected data onto subspaces with maximal "angular" separability in the input (raw) feature space and Reproducible Kernel Hilbert Space (RKHS). We also developed an angular locality preserving variant of this algorithm. In this letter, we advance this work and make it suitable for information fusion - we propose and validate a composite kernel local angular discriminant analysis projection, that can operate on an ensemble of feature sources (e.g. from different sources), and project the data onto a unified space through composite kernels where the data are maximally separated in an angular sense. We validate this method with the multi-sensor University of Houston hyperspectral and LiDAR dataset, and demonstrate that the proposed method significantly outperforms other composite kernel approaches to sensor (information) fusion.
Innovation and Income Inequality

The paper articulates and tests the hypothesis that innovation is a major factor in the reduction of income inequalities. The relationship between the pace of technological change and the dynamics of income inequalities has been first suggested by Kuznets (1955), but found little elaboration and empirical investigation in the subsequent literature. The evidence of a large data set including advanced countries, such as the US, Canada and the members of the European Union, as well as the newly industrializing BRIC members, in the years 1995-2011, confirms the virtuous circle between technological change and income inequalities.
Physical interaction between human and a bipedal humanoid robot-realization of human-follow walking

This research is aimed at the development of bipedal humanoid robots working in a human living space, with a focus on its physical construction and motion control method. At the first stage, we developed the bipedal humanoid robot WABIAN (Waseda bipedal humanoid), and proposed a control method for dynamic cooperative biped walking. In this paper, we present a follow-walking control method with a switching patterns technique for a bipedal humanoid robot to follow human motion by hand contact. By a combination of both algorithms, the robot is able to perform dynamic stepping and walking forward and backward in a continuous time while someone is pushing or pulling its hand. In this paper, the authors describe the control methods for the realization of physical interaction between a human and a bipedal humanoid robot.
A Multi Agent Approach for Texture Based Classification and Retrieval (MATBCR) using Binary Decision Tree

Texture Analysis has been used in a range of studies for recognizing synthetic and natural textures. We propose a simple, novel and yet effective method for classifying and retrieving images based on texture descriptor. In our system, the information needed for classifying the different types of textures are extracted from the Gabor features, Co-occurrence matrices and Law's Method. For Feature pre-selection the contextual merit algorithm is used along with the decision tree. For Multi-class classification, SVM with Binary Decision Tree is used. Canberra distance metrics is used for similarity computation. A Multi-Agent system consists of a group of distributed Texture agents that organize their knowledge, goals and plans. In addition, it supports relevance feedback. Our MATBCR model results have been compared with other Texture Based Retrieval System and better prediction accuracy has been observed.
Proceedings of the 2nd Workshop on Assessment of Contemporary Modularization Techniques (ACoM.08)

Common metrics of design modularity include coupling, cohesion, separation of concerns, etc. Large number of modularity assessment work has been done at the level of source code as retrospective empirical studies, but few at design level. In addition, these metrics are limited in terms of showing how tasks can be assigned to independent groups, and how the design enables parallel development. In fact, the term module used in traditional modularity assessment is not always consistent with Parnas’s canonical definition: independent task assignment. In this paper, we propose to measure modularity in design in term of independent task modules. The idea is to use design structure matrices to represent a design, automatically cluster the DSM to reveal independent modules, and assess to what extent the design can be independently implemented or changed.
A Multiple Access Scheme for the Uplink of MIMO Systems

In order to efficiently use the common channel resources in multi-user multiple-input and multiple- output (MIMO) systems, an independent component based multiple access (ICMA) scheme is introduced. In ICMA, the signals generated by different users are distinguished only from their independence, where neither non-interfering subchannels nor orthogonality constraints are needed. The scheme is based on independent component analysis (ICA) algorithm, which is a fundamental technique for blind source separation. The performance of the proposed receiver is compared with zero forcing (ZF) receiver and minimum mean-square error (MMSE) receiver. Simulation results show that ICMA receiver performs better than ZF receiver, and worse than MMSE receiver. However, in ICMA, there is no need of synchronization and channal estimation, which is required in ZF and MMSE. The efficiencies of the scheme are observed.
Toward Tacit Information Retrieval

Information Retrieval should be seen in the wider context of modern information society, in which knowledge-based activities have become predominant. Knowledge is now a crucial commodity and information retrieval techniques are very important in helping to find relevant information easily and quickly. Unfortunately there are various kinds of knowledge, and present computer techniques can only deal with explicit information, whereas many forms of knowledge are in fact tacit and accessible only through social interactions. We examine different varieties of knowledge and suggest ways to make them accessible by computer. By and large, the search for tacit knowledge may be replaced with a search for the right people, who can be found thanks to user profiling techniques. We present the example of a collaborative, distributed search system, which addresses some of the issues we have outlined. This system combines a peer-to-peer architecture with user profiling to create virtual communities so as to locate relevant knowledge. We then discuss the problems involved in implementing such a distributed system.
'You and your skin': a short-duration presentation of skin cancer prevention for teenagers.

The effectiveness of a short-duration presentation of the educational material 'You and Your Skin' was tested on 184 adolescents (age 13-15) at the Year 7 and 8 levels. A non-equivalent control group design was used with pre-testing and post-testing 3 months after the intervention. The intervention increased the students' knowledge of known risks factors for skin cancers. However, the students' attitudes to abstaining from sunbathing and tanning was not significantly affected. The effect of the intervention on the stage of change was primarily a progression from the precontemplation stage to the contemplation stage regarding avoiding the mid-day sun. We conclude that a brief presentation of the educational kit 'You and Your Skin' can be used to increase knowledge, but there is a need for a more extensive intervention effort to affect students' readiness to change their behavior and attitude towards sunbathing and tanning. Therefore, it is important to emphasize the necessity of using the educational kit as a multi-lesson programme with its several group exercises.