Miracle-dz/UniFAR-FTUs huggingface dataset:
2003 Annual Review of Development Effectiveness: The Effectiveness of Bank Support for Policy Reform

The Annual Review of Development Effectiveness (ARDE) 2003, examines the effectiveness of Bank support to borrower countries, in particular, the help to foster reform policies, and institutional frameworks. The Review focuses primarily, although not exclusively, on the years from 1999 through 2003. This is done to facilitate the juxtaposition of recent evaluation evidence with trends in policy indicators. Recent trends in developing countries ' policies suggest that the various dimensions of policy, and institutional performance have, on average, improved modestly, although recent reforms have touched most areas of development policy. In most countries that accomplished strong reform over the period 1999-2003, change was driven by necessity, or opportunities such as transition from socialism, economic crisis, European Union accession, and change of government. Development research suggests that such factors tend to galvanize support for change, and thus make the politics of policy reform easier. Countries whose policies improved over the period 1999-03, grew on average, at more than twice the rate of those that did not. Evaluation evidence links Bank support to recent improvements in policy. At the project level, good country policy ratings tend to be associated with good evaluation ratings on project outcomes. The Bank was less successful in linking its support to policy reform, in countries with no, or weak track records, or with deteriorating policy environments. The uncertainties associated with policy reform are reduced, when the Bank ' s support is aligned with country priorities that have been validated through country-led, inclusive political processes. A start has been made through the Poverty Reduction Strategy (PRSP) process. However, the PRSP ' s potential as a vehicle for fostering country ownership is undermined, according to some borrowing countries, by its role as condition for access to external financial assistance. And, in countries where recent outcomes of Bank assistance were evaluated as satisfactory, high quality, relevant, and timely, Economic and Sector Work (ESW) generally made a substantial contribution. Therefore , it is suggested the Bank should not normally engage in lending, before ESW has established a base of county and sector knowledge.
Constructing a Dataspace Based on Metadata and Ontology for Complicated Scientific Data Management

As data sharing and integration has the properties of data heterogeneity, semantic relationship, dynamicity, and immediate efficiency, dataspace has been proposed as a data management approach for diverse applications. This paper introduces a framework of constructing a dataspace based on metadata and ontology, especially for complicated scientific data management. Firstly, supported by the ontology, this method sets up a metamodel independent from the various platforms of data sources, and then applies the metamodel to describe the participants of the dataspace and the relationship between them, that is producing metadata to describe the dataspace. Based on the unified metadata, the search and query service can be provided for all the data within the dataspace.
Return on Roller Coasters: A Model to Guide Investments in Theme Park Attractions

Despite the economic significance of the theme park industry and the huge investments needed to set up new attractions, no marketing models exist to guide these investment decisions. This study addresses this gap in the literature by estimating a response model for theme park attendance. The model not only determines the contribution of each attraction to attendance, but also how this contribution is distributed within and across years. The model accommodates saturation effects, which imply that the impact of a new attraction is smaller if similar attractions are already present. It also captures reinforcement effects, meaning that a new attraction may reinforce the drawing power of similar extant attractions, especially when these were introduced recently. The model is calibrated on 25 years of weekly attendance data from the Efteling, a leading European theme park. Our return on investment calculations show that it is more profitable to invest in multiple smaller attractions than in one big one. This finding is in remarkable contrast with the current “arms race” in the industry. Furthermore, even though thrill rides tend to be more effective than theme rides, there are conditions under which one should consider to switch to the latter.
Filesystems for Streaming Databases

Workloads for high-performance streaming databases often contain many writes of small data blocks (for example, of metada t ) followed by large subrange queries. Most of today’s file syst ems and databases either cannot provide adequate performance f or the write phase, the read phase, or both. The supercomputing tec hnologies group at MIT CSAIL has been investigating cache-aware a nd cache-oblivious data structures for disk-resident stream ing data. We investigated the cache-aware buffered repository tree ( BRT). A BRT with a block size ofB can theoretically perform a write in time O((logB n)/ √ B), as compared to B-tree’s O(logB N), and can perform reads only a constant factor slower than the B-tree. W implemented a prototype of a cache-aware streaming B-tree. For 1megabyte blocks the streaming B-tree achieves a 230-fold sp eedup for random insertions, at a cost of slowing down serial inser tions by factor of 6. Preliminary measurements on the SSCA#3 IO bench mark show a 1.4-fold speedup using stream B-trees instead of standard B-trees. We have also designed a cache-oblivious data s tructure called the cache-oblivious lookahead tree, which shou ld be able to achieve similar bounds without requiring us to tune f or the
An Approach for Comparison of Methodologies for Estimation of the Financial Risk of a Bond , Using the Bootstrapping Method

The Ford Motor Company’s current cash holdings of approximately $25B are primarily invested in bonds with maturities ranging from a few months to five years. Due to the large size of this cash holding, losses in the bond market could result in a substantial negative impact to quarterly profits. To gauge the size of this risk, the Portfolio Management Department in Treasury, uses a program called RiskManager, which utilizes a concept called value at risk (VaR). VaR summarizes the expected maximum loss to a financial portfolio under various conditions. The value at risk methodology rests upon a number of assumptions about the behavior and statistical properties of financial market variables. One important component of a VaR model is how it measures the fluctuations in value (volatility) of market instruments like bonds. The accuracy of these volatility estimates directly affects the end-user’s confidence in the risk level determined by the VaR calculation. We have applied the statistical methodology called bootstrapping to compare the accuracy of the volatility estimates usable in the VaR model. In this report, we look at the meaning of VaR, including aspects of its calculation methodology. Then we introduce the bootstrapping method. Bootstrapping allows one to infer the standard error of statistical parameters based upon a limited sample size. Using the bootstrapping method we can approximate the standard error of the volatility measure used in VaR, and so make an estimate of the potential error in the VaR value itself. In other words, we gauge how reliable the risk level indicated using VaR is. We determine, for a sample historical period, the standard error of five different possible volatility estimates for VaR using the bootstrapping method. This allows us to examine if there is a better (lower standard error) approach that could be used in volatility estimation. Finally, we conduct backtesting to check the bootstrapping result by using one year of historical data. Based upon the bootstrapping method using limited historical data for a five-year bond, we have found the best volatility estimate to be one based on the simple variance of past results. This is in contrast to the method used in RiskManager, which is an exponentially weighted moving average technique. However, the variance technique, in our limited backtesting analysis, was found to be somewhat conservative in predicting risk, while the other was overly aggressive. We conclude that in practice, the difference between the two methodologies is relatively small, and would not drive substantially different risk management behavior.
Multilayer grown high-Q on-chip inductor for RF applications

In this paper a multi-layer grown spiral inductor is presented with higher Quality factor by 72% and self resonance frequency (SRF) by 17%, over planar spiral inductors for RF applications at 3.65 GHz. Higher Quality factor of multi layer inductor over planar inductor is obtained at higher order frequencies for smaller outer diameters by taking substrate loss into consideration. There is no significant change in inductance for both the inductors. The area of cross-section for the proposed inductor is 420μm×420μm. Proposed Multi layer inductor is designed on silicon substrate and shape of conductor is considered as rectangular for simple and accurate analysis. Proposed inductor is designed and simulated in HFSS V12 for obtaining Quality factor and Inductance. Proposed inductor can be performed up to GHz frequency range and is efficiently suitable for Microwave/RF and wireless communication applications.
POTENTIAL PREDICTABILITY OF THE MADDEN–JULIAN OSCILLATION

JANUARY 2003 AMERICAN METEOROLOGICAL SOCIETY | S ince its discovery by Madden and Julian (1971, 1972) over two decades ago, the Madden–Julian oscillation (MJO) has continued to be a topic of significant interest due to its complex nature (Madden and Julian 1994) and the wide range of phenomena with which it interacts. The onset and break activity of the Asian–Australian monsoon system is strongly influenced by the propagation and evolution of MJO events (e.g., Yasunari 1980; Lau and Chan 1986; Hendon and Liebmann 1990a,b). Apart from this significant local influence, there are also important downstream influences that arise from the MJO. For example, the development of persistent North Pacific circulation anomalies during Northern Hemisphere winter has been linked to the evolution and eastward progression of convective anomalies associated with MJO events (e.g., Weickmann 1983; Liebmann and Hartman 1984; Weickmann et al. 1985; Ferranti et al. 1990; Lau and Philips 1986; Higgins and Schubert 1996; Higgins and Mo 1997; Mo 2000). In fact, a link has been shown to exist between rainfall variability along the western United States, including extreme events, and the longitudinal position of MJO convective anomalies (Mo and Higgins 1998a,b; Jones 2000; Higgins et al. 2000; Whitaker and Weickmann 2001). In addition, MJO convective activity has been linked to Northern Hemisphere summertime precipitation variability over Mexico and South America as well as to wintertime circulation anomalies over the Pacific–South American sector (Nogues-Paegle and Mo 1997; Mo and Higgins 1998c; Jones and Schemm 2000; Paegle et al. 2000). Recently, studies have also shown that particular phases of the MJO are more favorable than others in regards to the development of tropical storms/hurricanes in both the Atlantic and Pacific sectors (Maloney and Hartmann 2000; Mo 2000; Higgins and Shi 2001). Finally, the passage of POTENTIAL PREDICTABILITY OF THE MADDEN–JULIAN OSCILLATION
Automatic multiple faces tracking and detection using improved edge detector algorithm

The automatic face tracking and detection has been one of the fastest developing areas due to its wide range of application, security and surveillance application in particular. It has been one of the most interest subjects, which suppose but yet to be wholly explored in various research areas due to various distinctive factors: varying ethnic groups, sizes, orientations, poses, occlusions and lighting conditions. The focus of this paper is to propose an improve algorithm to speed up the face tracking and detection process with the simple and efficient proposed novel edge detector to reject the non-face-likes regions, hence reduce the false detection rate in an automatic face tracking and detection in still images with multiple faces for facial expression system. The correct rates of 95.9% on the Haar face detection and proposed novel edge detector, which is higher 6.1% than the primitive integration of Haar and canny edge detector.
Impaired absorption of cholesterol and bile acids in patients with an ileoanal anastomosis

Background—No data exist on cholesterol absorption in patients with an ileoanal anastomosis (IAA). Aims—To study cholesterol absorption and its effects on cholesterol and bile acid metabolism in patients with an IAA. Patients and methods—Cholesterol absorption, and serum, biliary, and faecal lipids were studied in 24 patients with an IAA and 20 controls. Results—Fractional cholesterol absorption was significantly lower in the patients (36% versus 47% in controls). Surprisingly, the calculated intestinal influx of endogenous cholesterol was reduced so that the absolute absorption of cholesterol was decreased; elimination of cholesterol as faecal neutral steroids remained normal. Thus, the slightly increased cholesterol synthesis was mainly due to increased faecal bile acid excretion, which, in turn, was associated with reduced absorption and biliary secretion of bile acids. Serum total and low density lipoprotein (LDL) cholesterol and LDL triglycerides were lower in the patients. Molar percentage and saturation index of biliary cholesterol were slightly higher in patients with an IAA. Proportions of secondary bile acids in bile and faeces were diminished, and faecal unidentified bile acids were higher in patients. Conclusions—Cholesterol absorption is significantly impaired in patients with an IAA, and is closely related to changes in serum and biliary lipids observed in these patients.
Selective super-resolution via sparse representations of sharp image patches using multiple dictionaries and bicubic interpolation

This paper proposes an extension to the algorithm of single-image super-resolution based on selective sparse representation over a set of coupled low and high resolution dictionary pairs. The extended algorithm reserves the sparse representation framework for patches of high sharpness values while bicubic interpolation is used to super-resolve un-sharp patches. A set of cluster dictionary pairs is used for the super-resolution process. If a patch belong to a low sharpness cluster, it is super-resolved using bicubic interpolation. Otherwise, the this patch is sparsely coded over the cluster's low resolution dictionary. Then, the sparse coding coefficients of the low resolution patch along with the cluster's high resolution patch are used to estimate the corresponding high resolution patch. It is found empirically that a large percentage of patches have low sharpness values. Therefore, the usage of bicubic interpolation significantly reduces the super-resolution computational complexity, without sacrificing the reconstruction quality. Experimental results conducted over several images validate this result in terms of the PSNR and SSIM measures.
Trust Management in Emergency Networks

We study the unique trust management, and more precisely reputation management and revocation of malicious ad hoc nodes used for emergency communications.Unlike in centralized systems, reputation management and revocation in ad hoc networks is non-trivial. This difficulty is due to the fact that the nodes have to collaboratively calculate the reputation value of a particular node and then revoke the node if the reputation value goes below a threshold. A major challenge in this scheme is to prevent a malicious node from discrediting other genuine nodes. The decision to revoke a node has to be communicated to all the nodes of the network. In traditional ad hoc networks the overhead of broadcasting the message throughout the network may be very high. We solve the problem of reputation management and node revocation in ad hoc networks of cell phones by using a threshold cryptography based scheme. Each node of the network would have a set of anonymous referees which would store the reputation information of the node and issue reputation certificates to the node with timestamps. The misbehavior of a particular cell phone is reported to its anonymous referees, who issue certificates which reflect the positive and negative recommendations.
A Fokker-Planck differential equation approach for the zero-dispersion optical fiber channel

Optical fiber channels modeled by the stochastic nonlinear Schrödinger equation and operating at zero dispersion are considered in this paper. As a result of the Kerr nonlinearity and its interaction with amplified spontaneous emission noise, the amplitude and phase channels correlate with each other and the statistics of the received signal are non-Gaussian. In order to find the capacity of such a nonlinear channel, one must find the conditional probability density function (PDF) of the channel output given channel input. The complex zero-dispersion channel (viewed as an instance of the Langevin equation) is transformed to polar coordinates using Itô calculus, where the cubic nonlinearity appears to be more tractable. A method is introduced based on the Fokker-Planck differential equation, known in the statistical physics, to describe the PDF of the received signal.
Complete Nucleotide Sequence of the pCTX-M 3 Plasmid and Its Involvement in Spread of the Extended-Spectrum-Lactamase Gene bla CTX-M-3

Complete Nucleotide Sequence of the pCTX-M3 Plasmid and Its Involvement in Spread of the Extended-Spectrum -Lactamase Gene blaCTX-M-3 M. Gołębiewski,† I. Kern-Zdanowicz,* M. Zienkiewicz,‡ M. Adamczyk, J. Żyliǹska, A. Baraniak, M. Gniadkowski, J. Bardowski, and P. Cegłowski Department of Microbial Biochemistry, Institute of Biochemistry and Biophysics, Polish Academy of Sciences, and National Medicines Institute, Warsaw, Poland
Elimination Algorithm of Redundant Association Rules Based on Domain Knowledge

Many association rule mining algorithms have been developed to extract interesting patterns from large databases. However, a large amount of knowledge explicitly represented in domain knowledge has not been used to reduce the number of association rules. A significant number of known associations are unnecessarily extracted by association rule mining algorithms. The result is the generation of hundreds or thousands of non-interesting association rules. This paper presents an algorithm named DKARM, which takes into account not only database itself, but also related domain knowledge, so as to eliminate extraction of known associations in domain knowledge. Experiments show this algorithm can reasonably eliminate redundant rules, and effectively reduce the number of rules.
Utilizing High-level Visual Feature for Indoor Shopping Mall Navigation

Towards robust and convenient indoor shopping mall navigation, we propose a novel learning-based scheme to utilize the high-level visual information from the storefront images captured by personal devices of users. Specifically, we decompose the visual navigation problem into localization and map generation respectively. Given a storefront input image, a novel feature fusion scheme (denoted as FusionNet) is proposed by fusing the distinguishing DNN-based appearance feature and text feature for robust recognition of store brands, which serves for accurate localization. Regarding the map generation, we convert the user-captured indicator map of the shopping mall into a topological map by parsing the stores and their connectivity. Experimental results conducted on the real shopping malls demonstrate that the proposed system achieves robust localization and precise map generation, enabling accurate navigation.
Gender identification of the speaker using DTW method

This paper aims at automatically recognition of the gender through the speech signal being independent from the speaker. In this study it is purposed to decide the gender of the speaker by evaluating the distance of MFCC feature vectors. DTW method has been used to warp the time series in the process of evaluating of the distance. As a test data, as well as the speech recordings consisting of one word, the sentences consisting more than one word have been used. The test data are consisted of the records in which speakers' languages are different such as Turkish, English and German. The results of the test experimented in the study show that the accuracy is % 100 in the state of one-word while the accuracy is % 98 in the state of more than one- word.
NEW VIEWS OF INNOVATION SYSTEMS

The objective of this first survey paper is to improve the theory of innovation systems from the perspective of the ‘Knowledge Infrastructure’ with its wealth of public and private agents, including research and technology organizations, universities and consultancies. It is argued that analysing these institutions as part of the knowledge infrastructure will significantly further the theory of multi-agent innovation dynamics within innovation systems. The paper considers the evolution of innovation dynamics over the last 30 years and focuses on the contributions of the EU RTD Framework Programmes on innovation theory. It highlights the role of new types of agents, new kinds of organizational, institutional and cultural innovation as well as the process character of innovation dynamics.
Oil and S&P 500 Markets: Evidence from the Nonlinear Model

This study begins by using a MTAR model to explore the asymmetric effects of error corrections between oil prices in the U.S.A and S&P 500 prices under different regimes. After confirming the lead/lag relationship between the S&P 500 and oil prices, we employ a STECM to analyze the short-run return dynamics when there are deviations from the equilibrium between the two variables. Our empirical evidence shows that an asymmetric co-integration relationship exists between the S&P 500 and oil prices. In addition, the results of the Granger causality test based on the TECM document the unidirectional relationship from the oil price to the S&P 500 price. Moreover, the short-run adjustments of the mean reversion to equilibrium follow the LSTECM. The contribution of this study might be in that the LSTECM-GARCH model is well suited to describing the short-run return dynamics of the disequilibrium between the oil prices and S&P 500 prices in the U.S.A.
Cross-domain paraphrasing for improving language modelling using out-of-domain data

In natural languages the variability in the underlying linguistic generation rules significantly alters the observed surface word sequence they create, and thus introduces a mismatch against other data generated via alternative realizations associated with, for example, a different domain. Hence, direct modelling of out-of-domain data can result in poor generalization to the indomain data of interest. To handle this problem, this paper investigated using cross-domain paraphrastic language models to improve in-domain language modelling (LM) using out-ofdomain data. Phrase level paraphrase models learnt from each domain were used to generate paraphrase variants for the data of other domains. These were used to both improve the context coverage of in-domain data, and reduce the domain mismatch of the out-of-domain data. Significant error rate reduction of 0.6% absolute was obtained on a state-of-the-art conversational telephone speech recognition task using a cross-domain paraphrastic multi-level LM trained on a billion words of mixed conversational and broadcast news data. Consistent improvements on the in-domain data context coverage were also obtained. Copyright © 2013 ISCA.