Miracle-dz/UniFAR-FTUs huggingface dataset:
On-line hydraulic state prediction for water distribution systems

This paper describes and demonstrates a method for on-line hydraulic state prediction in urban water networks. The proposed method uses a Predictor-Corrector (PC) approach in which a statistical data-driven algorithm is applied to estimate future water demands, while near real-time field measurements are used to correct (i.e., calibrate) these predicted values on-line. The calibration problem is solved using a modified Least Squares (LS) fit method. The objective function is the minimization of the least-squares of the differences between predicted and measured hydraulic parameters (i.e., pressure and flow rates at several system locations), with the decision variables being the consumers’ water demands. The a-priori estimation (i.e., prediction) of the values of the decision variables, which improves through experience, facilitates a better convergence of the calibration model and provides adequate information on the system’s hydraulic state for real time optimization. The proposed methodology is demonstrated on a prototypical municipal water distribution system.
Concept based document management in cloud storage

Cloud computing is one of the most useful environment that provides various information services in which required information can be retrieved through many web-based tools and applications. Now the new surge of interest in cloud computing is accompanied with the exponential growth of data sizes. There is a need to find the desired content quickly and efficiently by simply consulting the index. Thus there arises a question of how to effectively process these immense data sets is becoming increasingly urgent. Our existing system is searching the content through ontology in cloud which practically suffers from maintaining a consistent logic for the input documents given and taking this advantage into consideration we have brought in new concepts called Document Retrieval Algorithm. In this paper we discuss how effectively and efficiently information can be retrieved from cloud taking into account their storage space too, where we store the metadata of file in cloud and not the entire file which holds a lot of space in distributed environment. Thus we bring in the concept of Named Entity Recognition and Universal Word List with Term frequency, which maximizes the information retrieval more effective and efficient and also to bridge the gap between the semantic web and the users which reduces the complexity met by them in information retrieval.
CMOS dynamic power estimation based on collapsible current source transistor modeling

When estimating the dynamic power dissipated by a circuit di erent methods ranging from numeric analog simulation to event-driven logic simulation have been proposed. However, as the technology reaches the deep sub-micron range, additional e ects as the short circuit current, partial voltage swings, transient behavior between clock cycles and leak current are becoming more relevant to achieve an accurate estimation of the consumption. In this paper we present Meiga, an event-driven simulation-based power estimator that accounts for power dissipation due to short circuit current, partial swings and transient behavior. Experiments have shown that circuits in the order of several thousands of transistors are simulated in seconds of CPU per input vector.
Coxsackievirus B3, Shandong Province, China, 1990–2010

To determine the cause of a 2008 outbreak of aseptic meningitis in Shandong Province, China, we analyzed samples from outbreak patients and coxsackievirus B3 samples collected during 1990–2010 surveillance. The cause of the outbreak was coxsackievirus B3, genogroup D. Frequent travel might increase importation of other coxsackievirus B3 genogroups.
Discourses of Postcolonialism in Contemporary British Children's Literature

1. The Politics of Children's Literature 2. The Empire Within: Migrant and Post-Migrant Coming-of-Age Novels 3. Rewriting Colonial Histories in Historical Fictions For the Young: From Below and Above 4. "Empires of the Mind": Intersections of Children's Fantasy and Postcolonialism 5. The (Post)Colonial Exotic: Representing the Other in Adventure Stories for the Young
Electricity Prices and Energy Efficiency - A Regression Discontinuity Approach

This study analyzes the relationship between electricity prices and energy efficiency in German companies. Economic theory suggests that higher energy prices will lead to higher energy efficiency. This paper tests this hypothesis empirically by analyzing company-level data from Germany. In particular, a special provision of the German Renewable Energy Act (REA) is exploited. According to this provision, some companies are exempted from paying the “REA markup” - a markup charged on the electricity price in order to finance subsidies for renewable energy. Exempted companies pay lower electricity prices and can therefore be used as a counterfactual in a regression discontinuity analysis. The results of the analysis suggest that energy prices have a statistically significant and positive effect on energy efficiency.
Improved ROVER using Language Model Information

In the standard approach to speech recognition, the goal is to find the sentence hypothesis that maximizes the posterior probability of the word sequence given the acoustic observation. Usually speech recognizers are evaluated by measuring the word error so that there is a mismatch between the training and the evaluation criterion. Recently, algorithms for minimizing directly the word error and other task specific error criterions have been proposed. This paper presents an extension of the ROVER algorithm for combining outputs of multiple speech recognizers using both a word error criterion and a sentence error criterion. The algorithm has been evaluated on the 1998 and 1999 broadcast news evaluation test sets, as well as the SDR 1999 speech recognition 10 hour subset and consistently outperformed the standard ROVER algorithm. The approach seems to be of particular interest for improving the recognition performance by combining only two or three speech recognizers achieving relative performance improvements of up to 20% compared to the best single recognizer.
Critical success factors enhancing enterprise resource planning systems implementation in Jordanian SMEs

Enterprise Resource Planning (ERP) is designed to model and automate basic processes across the organization over a centralized database sheet, or any type of tools that are used by the organization and pays a lot of attention in implementing ERP modules. The success of ERP system does not require the demolishing of the traditional ERP system models, but instead re-plat forming and hosting them. ERP application is often viewed as a strategic investment that can provide significant competitive advantage with positive return thus contributing to the company's revenue and growth. Despite such strategic importance given to ERP the implementation success to achieve the desired goal has been viewed disappointing. Industry encountered stories failures in ERP initiatives, despite numerous benefits. This study review the literature in ERP focusing on the trends or factors which may help future ERP initiatives achieve greater success and less failure.
Research on the Computing Framework in Big Data Environment

Computing framework is one of the key technologies in improving data analytics and processing efficiency. Since open source big data computing platform Hadoop was born ten years ago, many research achievements have been made in information acquisition, analytical processing and integrated services. Several improved frameworks were proposed against the limitations of the first generation of Map Reduce version 1 (MRv1) in scalability, reliability, efficient utilization of resource, and multiple computing model supports. This paper presents and analyzes these research results, such as batch computing framework, iterative computing framework, interactive computing framework, stream computing framework, and real-time computing framework. Undoubtedly, more targeted computing models will be generated in different application fields in the future, and these computing frameworks will play an increasingly important role in the field of big data.
Appearance-Based Virtual-View Generation for Fly Through in a Real Dynamic Scene

We present appearance-based Virtual view generation which allows viewers to fly through a real dynamic scene. The scene is captured by synchronized multiple cameras. Arbitrary views are generated by interpolating two original camera-view images near the given viewpoint. The quality of the generated synthetic view is determined by the precision, consistency and density of correspondences between the two images. All or most of previous work that uses interpolation extracts the correspondences from these two images. However, not only is it difficult to do so reliably (the task requires a good stereo algorithm), but also the two images alone sometimes do not have enough information, due to problems such as occlusion. Instead, we take advantage of the fact that we have many views, from which we can extract much more reliable and comprehensive 3D geometry of the scene as a 3D model. The dense and precise correspondences between the two images, to be used for interpolation, are derived from this constructed 3D model. Our method of 3D modeling from multiple images uses the Multiple Baseline Stereo method and Shape from Silhouette method.
Pre-bid network analysis for transportation procurement auction under stochastic demand

Transportation procurement is one of the most critical sourcing decisions to be made in many companies. This thesis addresses a real-life industrial problem of creating package bids for a company's transportation procurement auction. The purpose of offering package bids is to increase the carriers' capacity and to improve the reliability of services. In this thesis, we investigate the possibility of forming packages using the company's own distribution network. Effective distribution of packages requires balanced cycles. A balanced cycle is a cycle containing no more than 3 nodes with equal loads (or volume of package) on every link in the cycle. We develop mixed-integer programs to find the maximum amount of network volume that can be covered by well-balanced cycles. These models are deterministic models that provide a rough guide on the optimal way of package formation when loads are known in advance. Since demand is random in real life, we perform a stochastic analysis of the problem using various techniques including simulation, probabilistic analysis and stochastic programming. Results from the stochastic analysis show that the effectiveness of package distribution depends on how we allocate the volumes on the lanes to create balanced cycles. If we always assign a fixed proportion of the lanes' volumes to the cycles, then it is only possible to have well-balanced cycles when the average volumes on the lanes are very large, validating the advantage of joint bids between several companies. However, if we assign a different proportion of the lanes' volumes to the cycles each time demand changes, then it is possible to create cycles that are balanced most of the time. An approximated solution method is provided to obtain a set of balanced cycles that can be bid out. Thesis Supervisor: David Simchi-Levi Title: Professor of Civil and Environmental Engineering
Cultural influence on user preference on groupware application for intercultural collaboration

This paper discusses an ongoing research on how cultural dimensions affect user's preference in intercultural collaboration using a groupware application as a remote collaboration tools. This research will try to analyze how culture influences the way users prefer to interact using a computer application as the media by applying the Technology Acceptance Model that was introduced by Davis (1989) and utilizing four cultural dimensions, which are Collectivist-Individualist, Power Distance Index, Uncertainty Avoidance, and Low- and High Context communication from Hofstede, Gudykunst, Triandis, and Edward T.Hall. This paper will proposes how cultural dimensions should be applied when designing a synchronous groupware application as a remote collaboration tool aimed for multicultural users.
Sefidi The Influence of Forest Management Histories on Dead W ood and Habitat Trees in the Old Growth Forest in Northern Iran

Dead wood and habitat tree such as fallen logs, snags, stumps and cracks and loos bark etc. are regarded as an important ecological component of forests on which many forest dwelling species depend on presence of them within forest ecosystems. Meanwhile its relation to management history in Caspian forest has gone unreported. The aim of research was to compare the amounts of dead wood and habitat trees in the forests with historically different intensities of management, including: forests with the long term implication of management (PS), the short term implication of management (NS) which were compared with semi virgin forest (GS). The number of 405 individual dead and habitat trees were recorded and measured at 109 sampling locations. ANOVA revealed volume of dead tree in the form and decay classes significantly differ within sites and dead volume in the semi virgin forest significantly higher than managed sites. Comparing the amount of dead and habitat tree in three sites showed that, dead tree volume related with management history and significantly differ in three study sites. Meanwhile, frequency of habitat trees was significantly different within sites. The highest amount of habitat trees including cavities, cracks and loose bark and fork split trees was recorded in virgin site and lowest recorded in the sites with the long term implication of management. It can be concluded that forest management cause reduction of the amount of dead and habitat tree specially in a large size, thus managing this forest according to ecological sustainable principles require a commitment to maintaining stand structure that allow, continued generation of dead trees in a full range of size. Keywords—Cracks trees, forest biodiversity, fork split trees, nature conservation, sustainable management.
The Economic Analysis of Rent Seeking

This collection brings together the classic papers on the economics of rent seeking. These papers date from Gordon Tullockâ€™s original 1967 paper which first put forth the idea that the pursuit of transfers was socially costly. Other classic papers by Anne Krueger and Richard Posner are included, as well as a series of more recent papers which trace the evolution of the literature on this important innovation in economic theory.
Self tuning replication in transactional data grids

Partially replicated systems help to improve the scalability of replicated systems by allowing sites to store a subset of the application data and split the load among replicas, to maximize throughput. On the down side, data partitioning leads to the need of dealing with expensive remote data accesses, every time there is a retrieval of data not locally maintained. To cope with this problem several systems introduce an additional caching mechanism aimed at maintaining, at each node, a replica of the remote data items most frequently accessed by local transactions. However, when exposed to different workloads, caching mechanisms can also perform differently. This report proposes the development of an efficient, self-tuning caching mechanism for partially replicated transactional systems that aims at providing optimal performance when exposed to different workloads.
Co-transfer learning via joint transition probability graph based method

This paper studies a new machine learning strategy called co-transfer learning. Unlike many previous learning problems, we focus on how to use labeled data of different feature spaces to enhance the classification of different learning spaces simultaneously. For instance, we make use of both labeled images and labeled text data to help learn models for classifying image data and text data together. An important component of co-transfer learning is to build different relations to link different feature spaces, thus knowledge can be co-transferred across different spaces. Our idea is to model the problem as a joint transition probability graph. The transition probabilities can be constructed by using the intra-relationships based on affinity metric among instances and the inter-relationships based on co-occurrence information among instances from different spaces. The proposed algorithm computes ranking of labels to indicate the importance of a set of labels to an instance by propagating the ranking score of labeled instances via the random walk with restart. The main contribution of this paper is to (i) propose a co-transfer learning (CT-Learn) framework that can perform learning simultaneously by co-transferring knowledge across different spaces; (ii) show the theoretical properties of the random walk for such joint transition probability graph so that the proposed learning model can be used effectively; (iii) develop an efficient algorithm to compute ranking scores and generate the possible labels for a given instance. Experimental results on benchmark data (image-text and English-Chinese-French classification data sets) have shown that the proposed algorithm is computationally efficient, and effective in learning across different spaces. In the comparison, we find that the classification performance of the CT-Learn algorithm is better than those of the other tested transfer learning algorithms.
Secure deletion of data from magnetic and solid-state memory

With the use of increasingly sophisticated encryption systems, an attacker wishing to gain access to sensitive data is forced to look elsewhere for information. One avenue of attack is the recovery of supposedly erased data from magnetic media or random-access memory. This paper covers some of the methods available to recover erased data and presents schemes to make this recovery significantly more difficult.
The effect of cholesteryl ester transfer protein inhibition on lipids, lipoproteins, and markers of HDL function after an acute coronary syndrome: the dal-ACUTE randomized trial.

AIMS The effects of cholesteryl ester transfer protein (CETP) inhibition on lipids, inflammation, and markers of high-density lipoprotein (HDL) function, following an acute coronary syndrome (ACS), are unknown. METHODS AND RESULTS The dal-ACUTE study randomized 300 patients (1 : 1) to dalcetrapib 600 mg/day or placebo within 1 week of an ACS. The primary endpoint was per cent change in HDL-cholesterol (HDL-C) after 4 weeks. Secondary endpoints included apolipoprotein levels, markers of HDL function, and inflammation. Dalcetrapib treatment increased HDL-C and apolipoprotein A1 by 33.7 and 11.8%, respectively (both P < 0.001) and total cholesterol efflux by 9.5% (P = 0.003) after 4 weeks, principally via an increase in non-ATP-binding cassette transporter (ABC) A1-mediated efflux, without statistically significant changes in pre-β1-HDL levels. The increase in total efflux with dalcetrapib correlated most strongly with increases in apolipoprotein A1 and HDL-C (r = 0.46 and 0.43, respectively) rather than the increase in pre-β1-HDL (r = 0.32). Baseline and on-treatment ABCA1-mediated efflux correlated most strongly with pre-β1-HDL levels; in contrast, non-ABCA1-mediated efflux correlated better with apolipoprotein A1 and HDL-C levels. CONCLUSIONS High-density lipoprotein raised through CETP inhibition with dalcetrapib improves cholesterol efflux, principally via a non-ABCA1-mediated pathway. While HDL-C was increased by one-third, apolipoprotein A1 and total efflux were increased only by one-tenth, supporting the concept of dissociation between improvements in HDL function and HDL-C levels, which may be of relevance to ongoing trials and the development of therapeutic interventions targeting HDL.
How to grow a gut: ontogeny of the endoderm in the sea urchin embryo

Gastrulation is the process of early development that reorganizes cells into the three fundamental tissue types of ectoderm, mesoderm, and endoderm. It is a coordinated series of morphogenetic and molecular changes that exemplify many developmental phenomena. In this review, we explore one of the classic developmental systems, the sea urchin embryo, where investigators from different backgrounds have converged on a common interest to study the origin, morphogenesis, and developmental regulation of the endoderm. The sea urchin embryo is remarkably plastic in its developmental potential, and the endoderm is especially instructive for its morphological and molecular responsiveness to inductive cell interactions. We start by examining and integrating the several models for the morphogenetic mechanisms of invagination and tissue elongation, the basic processes of endoderm morphogenesis in this embryo. We next critique the proposed mechanisms of inductive gene regulation in the endoderm that exemplifies a concept of modular transcriptional regulation. Finally, we end with an examination of the current molecular models to explain cell fate determination of the endoderm. Recent progress at the molecular level should soon allow us to explain the seminal experimental observations made in this embryo over a hundred years ago. BioEssays 21:459–471, 1999. © 1999 John Wiley & Sons, Inc.
EpCAM/CD3-Bispecific T-cell Engaging Antibody MT110 Eliminates Primary Human Pancreatic Cancer Stem Cells

Purpose: Tumor-initiating cells with stem-like properties, also termed cancer stem cells (CSC), have been shown to sustain tumor growth as well as metastasis and are highly resistant to chemotherapy. Because pancreatic CSCs have been isolated on the basis of EpCAM expression, we investigated whether a targeted immunotherapy to EpCAM using the bispecific T-cell–engaging antibody MT110 is capable of eradicating CSCs. Experimental Design: We studied in vitro and in vivo the effects of MT110 on CSCs using both established cell lines as well as primary cells of human pancreatic cancer. Results: Although established cell lines were more responsive to MT110-engaged T cells, also primary cells showed a time- and dose-dependent response to treatment with the bispecific antibody. In addition, the population of highly tumorigenic CSCs was efficiently targeted by the EpCAM/CD3-bispecific antibody MT110 in vitro and in vivo using a mouse model of established primary pancreatic cancer. Pancreatic cancer cells derived from metastases were slightly more resistant to MT110 treatment on the basis of in vivo tumorigenicity studies. This appeared to be related to a higher frequency of an EpCAM-negative subpopulation of CSCs. Conclusions: Cytotoxic T cells can be effectively redirected against primary human pancreatic cancer cells by T-cell–engaging BiTE antibody MT110 including a subpopulation of highly tumorigenic CSCs. Clin Cancer Res; 18(2); 465–74. ©2011 AACR.
Testing University Rankings Statistically : Why this Perhaps is not such a Good Idea after All . Some Reflections on Statistical Power , Effect Size , Random Sampling and Imaginary Populations

In this paper we discuss and question the use of statistical significance tests in relation to university rankings as recently suggested. We outline the assumptions behind and interpretations of statistical significance tests and relate this to examples from the recent SCImago Institutions Ranking. By use of statistical power analyses and demonstration of effect sizes, we emphasize that importance of empirical findings lies in “differences that make a difference” and not statistical significance tests per se. Finally we discuss the crucial assumption of randomness and question the presumption that randomness is present in the university ranking data. We conclude that the application of statistical significance tests in relation to university rankings, as recently advocated, is problematic and can be misleading.