Miracle-dz/UniFAR-FTUs huggingface dataset:
Information overload: implications for healthcare services

Information overload is not a new phenomenon: the potential for it has existed ever since information became an important input to any human activity. For example, once the scientific disciplines began to clearly emerge in the seventeenth to the nineteenth centuries, it gradually became impossible for anyone to keep abreast of all of the work in what had been called ‘natural philosophy’. In some fields, the degree of specialization is so high that, even within the same discipline, people are unable to keep abreast of all subareas and, in fact, may be completely unable to understand some of them. This paper defines and analyses the phenomenon of information overload and seeks to present organizational therapies that address it.
Knowledge and Money: Research Universities and the Paradox of the Marketplace

Contents Introduction 1 1 Universities as Knowledge-Based Institutions 7 2 University Costs 28 3 Undergraduates 76 4 Academic Research 132 5 Universities, Industry, and Economic Development 180 6 Universities and Markets 232 Appendixes A. Costs per FTE Student, 1980, 1990, 2000 269 B. Research Share for Selected Universities, 1980, 1990, 2000 272 Notes 275 Index 317 Library of Congress Subject Headings for this publication: Research institutes Economic aspects United States, Research Economic aspects United States, Universities and colleges Economic aspects United States
Application of a Time-Frequency-Based Blind Source Separation to an Instantaneous Mixture of Secondary Radar Sources

In Secondary Surveillance Radar (SSR) systems, it is more difficult to locate and recognise aircrafts in the neighbourhood of civil airports since aerial traffic becomes greater. Here, we propose to apply a recent Blind Source Separation (BSS) algorithm based on Time-Frequency Analysis, in order to separate messages sent by different aircrafts and falling in the same radar beam in reception. The above source separation method involves joint-diagonalization of a set of smoothed version of spatial Wigner-Ville distributions. The technique makes use of the difference in the t f signatures of the nonstationary sources to be separated. Consequently, as the SSR sources emit different messages at different frequencies, the above method is fitted to this new application. We applied the technique in simulation to separate SSR replies. Results are provided at the end of the paper.
Alternative Theories of Small-Firm Growth: A Critical Review

This paper contains a review of alternative theories which have been developed in order to explain growth and change in the small manufacturing firm. Models of small-firm growth derived within the industrial economics literature are evaluated together with stage models of growth and stochastic models. Social and psychological perspectives on growth are reviewed and the spatial dimension is also considered. We argue that most previous theories of small-firm growth place too little emphasis upon the difficulties which small owner-managed firms have in meeting the competitive requirements of the marketplace.
Balancing and translation control of a ball segway that a human can ride

A ball segway, a ballbot-type robot that can carry a person is developed. The robot is of a sufficient size and has a car-like structure mounted on a single spherical tire with a seat that a human can ride. Based on the kinematic model of the ball segway, the full 3D dynamic model is simplified and decoupled into two orthogonal 2D dynamic models, where one is related sagittal motion and the other is related frontal motion, based on Lagrange equation and decoupling method. After linearizing dynamic model, two-loop control system is applied to each plane for control balancing, station keeping and transferring itself from point to point. Balancing and transferring performance of the ball segway is evaluated by experiments.
Image Segmentation Using Maximum Spanning Tree on Affinity Matrix

The objective of image segmentation and clustering is to extract meaningful regions out of an image. A graph theoretic approach, as an alternative to the gradient-based methods, is usually based on the eigenvectors of an affinity matrix [3,4,5,6,7]. The theoretical foundation of this development is the Spectral Graph Theory [1], through which the combinatorial features of a graph can be revealed by its spectra. This characteristic can be applied into graph partitioning and preconditioning. The typical eigendecompostion based segmentation work is called the normalized cuts [6]. The normalized cut measure incorporates the local similarity within cluster and total dissimilarity between clusters. The minimization of this measure is to solve the Rayleigh quotient, a generalized eigenvalue solving problem. However, solving a standard eigenvalue problem for all eigenvectors has exponential complexity and is very time consuming. Shi [6] made use of the sparsity of the affinity matrix and introduced the Lanczos method to simplify the computation of eigenvalues. In this paper, we give a new image segmentation algorithm using the maximum spanning tree [2]. Our method works on affinity matrix and addresses the physical meanings of an affinity matrix. Instead of computations of eigenvalues and eigenvectors, we proved that the image segmentation could be transformed into an optimization problem: finding the maximum spanning tree of the graph with image pixels as vertices and pairwise similarities as weights. Section 2 describes the related theory and Section 3 gives the experimental results on synthetic and real data to illustrate the performance of this algorithm. Finally, we draw a conclusion and discuss future work in Section 4.
Estimating High Dimensional Covariance Matrices and its Applications

Estimating covariance matrices is an important part of portfolio selection, risk management, and asset pricing. This paper reviews the recent development in estimating high dimensional covariance matrices, where the number of variables can be greater than the number of observations. The limitations of the sample covariance matrix are discussed. Several new approaches are presented, including the shrinkage method, the observable and latent factor method, the Bayesian approach, and the random matrix theory approach. For each method, the construction of covariance matrices is given. The relationships among these methods are discussed.
On biases in the predictions of stellar population synthesis models

Sampling fluctuations in stellar populations give rise to dispersion in observables when a small number of sources contribute effectively to the observables. This is the case for a variety of linear functions of the spectral energy distribution (SED) in small stellar systems, such as galactic and extragalactic H ii regions, dwarf galaxies or stellar clusters. In this paper we show that sampling fluctuations also introduce systematic biases and multimodality in non-linear functions of the SED, such as luminosity ratios, magnitudes and colours. In some cases, the distribution functions of rational and logarithmic quantities are bimodal, hence complicating the interpretation of these quantities considerably in terms of age or evolutionary stages. These biases can only be assessed by Monte Carlo simulations. We find that biases are usually negligible when the effective number of stars, N, which contribute to a given observable is larger than 10. Bimodal distributions may appear when N is between 10 and 0.1. Predictions from any model of stellar population synthesis become extremely unreliable for small N values. providing an operational limit to the applicability of such models for the interpretation of integrated properties of stellar systems. In terms of stellar masses, assuming a Salpeter initial mass function in the range 0.08-120 M O . , N = 10 corresponds to about 10 5 M O . (although the exact value depends on the age and the observable). This bias may account, at least in part, for claimed variations in the properties of the stellar initial mass function in small systems, and arises from the discrete nature of small stellar populations.
ePublius: Anonymous Speech Rights Online

The First Amendment to the U.S. Constitution prohibits Congress from abridging the freedom of speech, yet the text of the Amendment does not expressly address the issue of anonymous speech rights. Historical records from state ratifying conventions and from the First Congress do not discuss anonymous expression. Still, anonymous speakers and their works played an immensely important role in the founding era and throughout American history. This essay explores the interplay between the right to speak anonymously and the freedom of speech on the Internet. It concludes that the First Amendment also protects the right of individuals to speak anonymously online.
Inviscid coalescence of drops

We study the coalescence of two drops of an ideal fluid driven by surface tension. The velocity of approach is taken to be zero and the dynamical effect of the outer fluid (usually air) is neglected. Our approximation is expected to be valid on scales larger than $\ell_{\nu} = \rho\nu^2/\sigma$, which is 10 nm for water. Using a high-precision boundary integral method, we show that the walls of the thin retracting sheet of air between the drops reconnect in finite time to form a toroidal enclosure. After the initial reconnection, retraction starts again, leading to a rapid sequence of enclosures. Averaging over the discrete events, we find the minimum radius of the liquid bridge connecting the two drops to scale like $r_b \propto t^{1/2}$.
Design of logic circuits with wired-logic utilizing transduction method

Wired-logic is especially useful when designing fan-in restricted logic circuits which are implemented with bipolar and MOS transistors. There is, however, little published on the subject outside of the work done by the present authors. In this paper, a method of reducing the levels of circuits by utilizing Wired-Logic is presented. The method restricts the number of fanins for a gate utilizing Wired-Logic and transforms circuits using the transduction method optimization. To attain the proper combination of NOR gates and Wired-OR gates, an algorithm using Wired-OR gates for the fan-in restriction is also presented. By performing experiments on third level NOR circuits, the proposed method is comparable to Generalized Serial Duplication which is an efficient serial duplication. The levels of most circuits are reduced by Wired-OR gates, thereby demonstrating the efficiency of Wired-Logic. Although connection length is important to LSI, the cost function simplifies circuit levels. Hence, for the purposes of this paper, analysis is expanded to include the cost function.
Design Patterns for Developing High Efficiency Mobile Application

With the advent of technology, mobile devices are becoming powerful and they are widely used as convenient computing devices. In order to develop high quality application in a short period while overcoming the limitations and challenges in mobile development, strong knowledge and understanding of the design purpose are the key factors in developing well- designed applications. Good design ensures that crashes or harmful actions can be prevented as well as increasing users’ satisfaction. By implementing design patterns, developers can cater wide variety of users whereby they do not have to redevelop similar application for users who are using different types of devices. Application can be developed in a short period as developer can reuse design patterns to develop new application in similar domain. Our proposed work aims to implement design patterns to overcome limitations of current techniques and increase efficiency, usability and reusability in mobile application development.
Copper Price Discovery on Comex, the LME and the SHFE, 2001-2013

Over the past two decades, China has come to dominate international commerce in copper. The importance of the Shanghai Futures Exchange(SHFE) has increased in response to this development. We look at the distribution of price discovery between the SHFE and the two historically important copper futures exchanges, Comex and the LME. The resultsindicate that it is Comex, followed by the SHFE, not the LME which plays the most important role in copper price discovery. We also highlighta number of problems associated with both the calculation and interpretation of the standard IS and PT price discovery measures when used to look at overlapping price change on non-synchronous markets.The results offer a clearer interpretation in terms of trading slots (European, North American and Asian trading days) than in terms of exchanges.
Generic and Brand Advertising Strategies in a Dynamic Duopoly

To increase the sales of their products through advertising, firms must integrate their brand-advertising strategy for capturing market share from competitors and their generic-advertising strategy for increasing primary demand for the category. This paper examines whether, when, and how much brand advertising versus generic advertising should be done. Using differential game theory, optimal advertising decisions are obtained for a dynamic duopoly with symmetric or asymmetric competitors. We show how advertising depends on the cost and effectiveness of each type of advertising for each firm, the allocation of market expansion benefits, and the profit margins determined endogenously from price competition. We find that generic advertising is proportionally more important in the short term and that there are free-riding effects leading to suboptimal industry expenditure on generic advertising that worsen as firms become more symmetric. Due to free-riding by the weaker firm, its instantaneous profit and market share can actually be higher. The effectiveness of generic advertising and the allocation of its benefits, however, have little effect on the long-run market shares, which are determined by brand-advertising effectiveness. Extensions of the model show that market potential saturation leads to a decline in generic advertising over time.
Interactive Visual Analysis of Scientific Data

In a growing number of application areas, a subject or phenomenon is investigated by means of multiple datasets being acquired over time (spatiotemporal), comprising several attributes per data point (multi-variate), stemming from different data sources (multi-modal) or multiple simulation runs (multi-run/ensemble) [KH13]. Interactive visual analysis (IVA) comprises concepts and techniques for a user-guided knowledge discovery in such complex data. Through a tight feedback loop of computation, visualization and user interaction, it provides new insight into the data and serves as a vehicle for hypotheses generation or validation. It is often implemented via a multiple coordinated view framework where each view is equipped with interactive drill-down operations for focusing on data features. Two classes of views are integrated: physical views, such as direct volume rendering, show information in the context of the spatiotemporal observation space while attribute views, such as scatter plots and parallel coordinates, show relationships between multiple data attributes. The user may drill-down the data by selecting interesting regions of the observation space or attribute ranges leading to a consistent highlighting of this selection in all other views (brushing-and-linking). Three patterns of explorative/analytical procedures may be accomplished by doing so. In a feature localization, the user searches for places in the 3D/4D observation space where certain attribute values are present. In a multi-variate analysis, relations between data attributes are investigated, e.g., by searching for correlations. In a local investigation, the user inspects the values of selected attributes with respect to certain spatiotemporal subsets of the observation space. In this tutorial, we discuss examples for successful applications of IVA to scientific data from various fields: climate research, medicine, epidemiology, and flow simulation / computation, in particular for automotive engineering. We base our discussions on a theoretical foundation of IVA which helps the tutorial attendees in transferring the subject matter to their own data and application area. In the course of the tutorial, the attendees will become acquainted with techniques from statistics and knowledge discovery, which proved to be particularly useful for a specific IVA application. The tutorial further comprises an overview of off-the-shelf IVA solutions, which may be be particularly interesting for visualization practitioners. It is concluded by a summary of the gained knowledge and a discussion of open problems in IVA of scientific data.
DEWS 2003 2-B-01 Effective load-balancing of peer-to-peer systems

The growing popularity of peer-to-peer (P2P) systems has necessitated the need for managing huge volumes of data efficiently to ensure acceptable user response times. Dynamically changing popularities of data items and skewed user query patterns in P2P systems may cause some of the peers to become bottlenecks, thereby resulting in severe load imbalance and consequently increased user response times. An effective load-balancing mechanism becomes a necessity in such cases. Such load-balancing can be achieved by efficient online data migration/replication. While much work has been done to harness the huge computing resources of P2P systems for high-performance computing and scientific applications, issues concerning load-balancing with a view towards faster access to data for normal users have not received adequate attention. Notably, the sheer size of P2P networks and the inherent dynamism of the environment pose significant challenges to load-balancing. The main contributions of our proposal are three-fold. First, we view a P2P system as comprising clusters of peers and present techniques for both intra-cluster and inter-cluster load-balancing. Second, we analyze the trade-offs between the options of migration and replication and formulate a strategy based on which the system decides at run-time which option to use. Third, we propose an effective strategy aimed towards automatic self-evolving clusters of peers. Our performance evaluation demonstrates that our proposed technique for inter-cluster load-balancing is indeed effective in improving the system performance significantly. To our knowledge, this work is one of the earliest attempts at addressing load-balancing via both online data migration and replication in P2P environments.
Semi-automated construction of decision rules to predict morbidities from clinical texts.

OBJECTIVE In this study the authors describe the system submitted by the team of University of Szeged to the second i2b2 Challenge in Natural Language Processing for Clinical Data. The challenge focused on the development of automatic systems that analyzed clinical discharge summary texts and addressed the following question: "Who's obese and what co-morbidities do they (definitely/most likely) have? ". Target diseases included obesity and its 15 most frequent comorbidities exhibited by patients, while the target labels corresponded to expert judgments based on textual evidence and intuition (separately). DESIGN The authors applied statistical methods to preselect the most common and confident terms and evaluated outlier documents by hand to discover infrequent spelling variants. The authors expected a system with dictionaries gathered semi-automatically to have a good performance with moderate development costs (the authors examined just a small proportion of the records manually). MEASUREMENTS Following the standard evaluation method of the second Workshop on challenges in Natural Language Processing for Clinical Data, the authors used both macro- and microaveraged Fbeta=1 measure for evaluation. RESULTS The authors submission achieved a microaverage F(beta=1) score of 97.29% for classification based on textual evidence (macroaverage F(beta=1) = 76.22%) and 96.42% for intuitive judgments (macroaverage F(beta=1) = 67.27%). CONCLUSIONS The results demonstrate the feasibility of the authors approach and show that even very simple systems with a shallow linguistic analysis can achieve remarkable accuracy scores for classifying clinical records on a limited set of concepts.
Multi-scale image registration based on strength correspondence weighted graph

This paper proposes a novel strength correspondence weighted graph for multi-scale image registration. First, the strength correspondence weighted graph is proposed based on the structure information and attributes relations of graph. Second, a similarity scale parameter obtained which can adjust adaptively scale based on the similarity of the different feature points. Third, the energy is embedded in the strength correspondence weighted graph, which not only considers distribution of the energy but also considers the level of energy, which can better describe the similarity between the features of the image and find the correspondence between the features. Experiments on real-word images demonstrate that the proposed method is effective and accurate for multi-scale image registration.
On closed constrained frequent pattern mining

Constrained frequent patterns and closed frequent patterns are two paradigms aimed at reducing the set of extracted patterns to a smaller, more interesting, subset. Although a lot of work has been done with both these paradigms, there is still confusion around the mining problem obtained by joining closed and constrained frequent patterns in a unique framework. In this paper, we shed light on this problem by providing a formal definition and a thorough characterization. We also study computational issues and show how to combine the most recent results in both paradigms, providing a very efficient algorithm which exploits the two requirements (satisfying constraints and being closed) together at mining time in order to reduce the computation as much as possible.
Strained Silicon Layer in CMOS Technology

Semiconductor industry is currently facing with the fact that conventional submicron CMOS technology is approaching the end of their capabilities, at least when it comes to scaling the dimensions of the components. Therefore, much attention is paid to device technology that use new technological structures and new channel materials. Modern technological processes, which mainly include ultra high vacuum chemical vapor deposition, molecular beam epitaxy and metal-organic molecular vapor deposition, enable the obtaining of ultrathin, crystallographically almost perfect, strained layers of high purity. In this review paper we analyze the role that such layers have in modern CMOS technologies. It’s given an overview of the characteristics of both strain techniques, global and local, with special emphasis on performance of NMOS biaxial strain and PMOS uniaxial strain. Due to the improved transport properties of strained layers, especially high mobility of charge carriers, the emphasis is on mechanisms to increase the charge mobility of strained silicon and germanium, in light of recent developments in CMOS technology.
Obstructions and lines of marginal stability from the world-sheet

The behaviour of supersymmetric D-branes under deformations of the closed string background is studied using world-sheet methods. We explain how lines of marginal stability and obstructions arise from this point of view. We also show why = 2 B-type branes may be obstructed against (cc) perturbations, but why such obstructions do not occur for = 4 superconformal branes at c = 6, i.e. for half-supersymmetric D-branes on K3. Our analysis is based on a field theory approach in superspace, as well as on techniques from perturbed conformal field theory.