Miracle-dz/UniFAR-FTUs huggingface dataset:
EXISTENCE OF AN EQUILIBRIUM FOR A COMPETITIVE ECONOMY

A. Wald has presented a model of production and a model of exchange and proofs of the existence of an equilibrium for each of them. Here proofs of the existence of an equilibrium are given for an integrated model of production, exchange and consumption. In addition the assumptions made on the technologies of producers and the tastes of consumers are significantly weaker than Wald's. Finally a simplification of the structure of the proofs has been made possible through use of the concept of an abstract economy, a generalization of that of a game. Introduction L. Walras [ 24 ] first formulated the state of the economic system at any point of time as the solution of a system of simultaneous equations representing the demand for goods by consumers, the supply of goods by producers, and the equilibrium condition that supply equal demand on every market. It was assumed that each consumer acts so as to maximize his utility, each producer acts so as to maximize his profit, and perfect competition prevails, in the sense that each producer and consumer regards the prices paid and received as independent of his own choices. Walras did not, however, give any conclusive arguments to show that the equations, as given, have a solution.
Semantic Operations for Transfer-based Machine Translation

Semantic Operations for Transfer-based Machine Translation Michael Wayne Goodman Co-Chairs of the Supervisory Committee: Chair Emily M. Bender Department of Linguistics Chair Francis Bond Division of Linguistics and Multilingual Studies, Nanyang Technological University This dissertation describes a new approach to the automatic extraction of semantic mappings (transfer rules) for rule-based machine translation. This approach continues previous work in combining HPSG rule-based grammars, whose precise bidirectional implementation facilitates deep semantic analysis of sentences and the enumeration of grammatical realizations of semantic representations, and data-driven techniques of machine translation, whose automatic extraction of knowledge and statistical inference allow models to be quickly built from bitexts and to rank extracted patterns by their frequency. I define two new methods for bilingually aligning semantic fragments (or semantic subgraphs) and a heuristic strategy for aligning nodes between source and target subgraphs, which together allow me to design transfer systems that meet, and at times exceed, the translation coverage and quality of the prior state of the art with a significantly reduced dependence on idiosyncratic language-pair definitions (i.e., improved language independence). These improvements are made possible by a number of semantic operations, either designed or implemented by me and defined within this dissertation, that fully model the semantic representations and allow for inspection and transformation as graph operations. I apply my methods to the task of translating Japanese sentences into English—a typologically distant language pair.
Identity matching in social media platforms

Identity matching is crucial in many scenarios such as profile integration, identity resolution, data enrichment, forensic sciences and national security. In this paper we propose a novel solution for finding and matching profiles of a single person among Facebook, Linkedin and Twitter social platforms. In our proposed framework we look beyond the simple profile attributes such as name and location and consider users' online shared material and social relationships. We utilize custom string matching algorithms, natural language processing and other web APIs to analyze and compare the profiles. Profiles with the similarity value above a threshold are considered matches.
Statistical multi-source translation

We describe methods for translating a text given in multiple source languages into a single target language. The goal is to improve translation quality in applications where the ultimate goal is to translate the same document into many languages. We describe a statistical approach and two specific statistical models to deal with this problem. Our method is generally applicable as it is independent of specific models, languages or application domains. We evaluate the approach on a multilingual corpus covering all eleven official European Union languages that was collected automatically from the Internet. In various tests we show that these methods can significantly improve translation quality. As a side effect, we also compare the quality of statistical machine translation systems for many European languages in the same domain.
MTTG: An efficient technique for test data generation

Test data generation is a significant part of software and/or hardware testing. It is a complex problem and researchers have proposed various solutions to generate optimum number of test data in an acceptable polynomial time. However, most of the solutions are highly complex (NP-hard), interaction limitation and takes substantial time to generate test data set. Therefore, it is an open challenge to propose the best solution. This paper proposes a novel technique called MTTG (Multi-Tuple based T-way Test Generator) which relies on Kid's Card game strategy. The proposed technique finds optimum matching value by searching through all possible combination of similarity matching, based on data generation principle. Our empirical results demonstrate that the proposed MTTG is very efficient in test data generation based on time and interaction strength/level, compared to other existing strategies.
Optimal Boundary Triangulations of an Interpolating Ruled Surface

We investigate how to define a triangulated ruled surface interpolating two polygonal directrices that will meet a variety of optimization objectives which originate from many CAD/CAM and geometric modeling applications. This optimal triangulation problem is formulated as a combinatorial search problem whose search space however has the size tightly factorial to the numbers of points on the two directrices. To tackle this bound, we introduce a novel computational tool called multi-layer directed graph and establish an equivalence between the optimal triangulation and the single-source shortest path problem on the graph. Well known graph search algorithms such as the Dijkstra’s are then employed to solve the single-source shortest path problem, which effectively solves the optimal triangulation problem in O(mn) time, where n and m are the numbers of vertices on the two directrices respectively. Numerous experimental examples are provided to demonstrate the usefulness of the proposed optimal triangulation problem in a variety of engineering applications.
Action Representation and Recognition

Recognizing human actions is an important and challenging topic in computer vision, withmany important applications including video surveillance, video indexing and understanding of social interaction. From a computational perspective, actions can be defined as four-dimensional patterns, in space and in time. Such patterns can be modeled using several representations which differ from each other with respect to, among others, the visual information used, e.g. shape or appearance, the representation of dynamics, e.g. implicit or explicit, and the amount of invariance that the representation exhibits, e.g. a viewpoint invariance allowing to learn and recognize using different camera configurations. Our goal in this thesis is to develop a set of new techniques for action recognition. In the first part we present "Motion History Volumes", a free-viewpoint representation for human actions based on 3D visual-hull reconstructions computed form multiple calibrated, and backgroundsubtracted, video cameras. Results indicate that this representation can be used to learn and recognize basic human action classes, independently of gender, body size and viewpoint. We then present in the second part an approach based on a 3D exemplar-based HMM, which addresses the problem of recognizing actions from arbitrary views, even from a single camera. We will thus no longer require a 3D reconstruction during the recognition phase, instead we will use learned 3D models to produce 2D image information, which is compared to the observations. In the third and last part, we present a compact and efficient exemplar-based representation, which in particular does not attempt to encode the dynamics of an action through temporal dependencies. In experimental results we demonstrate that such a representation can precisely recognize actions, even with cluttered and non-background-segmented sequences.
A Neural Reinforcement Learning System

In this paper we present a reinforcement learning (RL) system based on neural circuits. The neural RL system is benchmarked against a Monte Carlo (MC) RL algorithm on two tasks. The first task is the classical n-armed bandit problem and the second task is path finding in a maze. The neural RL system performs equally well or better than the MC RL algorithm. The RL system presented is very flexible and general; it can easily be incorporated with other neural based systems, e.g. attractor memories.
Automatic Detection of Pulmonary Nodules in Multi-slice CT Based on 3D Neural Networks with Adaptive Initial Weights

Detection of pulmonary nodules combined of extraction by multi-directions PCA and identification by 3D (three dimension) BP neural network is presented in the paper, which is different from most lung CAD algorithms, that it does not require any a priori information by human intervention but solely the information contained by the CT image itself, and it is capable to perform full automation which support the radiologists in their final decision. The technique is tested against 60 cases of different pulmonary nodules which are screened out by cancer experts. Results confirm the validity of technique as well as enhanced performance.
BirdFinder: Web search and audio search extension

BirdFinder is a bird search engine that applies concepts of information retrieval and Web 2.0 to allow nonexpert users to access information using text and audio search mechanisms. It integrates audio, images and identification characteristics related to the ornithology domain. Content is stored in a highly scalable NoSQL repository. The main contribution of this work is a software architecture and two complementary search mechanisms to access non-structured content. This paper presents an evaluation of the application using information retrieval relevance measures to evaluate the search performance. Evaluation shows a good performance for both search engines providing ground for further research.
ната мощност, fuzzy logic контролер GRID-CONNECTED PV SYSTEM WITH MPPT CONTROL

Резюме: В статията е описана фотоволтаична система, свързана към електрическата мрежа, която използва контролер за следене на точката на максималната мощност. Създаден е подробен симулационен модел на системата, заедно с управлението. Изследвани са алгоритми за следене на максималната мощност, основани на предефинирани криви и с размита (fuzzy) логика. Показани са резултати от симулациите, които доказват работоспособността на моделите при рязко променящи се метеорологични условия и адекватността на избраните подходи. Симулационните резултати от еднофазната система са сравнени с експериментални данни.
GPKEX: Genetically Programmed Keyphrase Extraction from Croatian Texts

We describe GPKEX, a keyphrase extraction method based on genetic programming. We represent keyphrase scoring measures as syntax trees and evolve them to produce rankings for keyphrase candidates extracted from text. We apply and evaluate GPKEX on Croatian newspaper articles. We show that GPKEX can evolve simple and interpretable keyphrase scoring measures that perform comparably to more complex machine learning methods previously developed for Croatian.
Effect of hemochromatosis genotype and lifestyle factors on iron and red cell indices in a community population.

BACKGROUND Heterozygotes for the C282Y mutation of the HFE gene may have altered hematology indices and higher iron stores than wild-type subjects. METHODS We performed a cross-sectional analysis of 1488 females and 1522 males 20-79 years of age drawn from the Busselton (Australia) population study to assess the effects of HFE genotype, age, gender, and lifestyle on serum iron and hematology indices. RESULTS Male C282Y heterozygotes had increased transferrin saturation compared with the wild-type genotype. Neither male nor female heterozygotes had significantly increased ferritin values compared with the wild-type genotype. Younger (20-29 years) wild-type males, but not heterozygous males, had significantly lower ferritin values than wild-type males in the older age groups. Compound heterozygous subjects had increased means for serum iron, transferrin saturation, corpuscular volume, and corpuscular hemoglobin compared with the wild-type genotype, and the males also had increased ferritin values (medians 323 vs 177 microg/L; P = 0.003). In both male and female wild-type subjects, an increased body mass index was associated with decreased serum iron and transferrin saturation and increased ferritin values. There was a significant increase in ferritin concentrations in both genders with increasing frequency of red meat consumption above a baseline of 1-2 times per week and alcohol intakes >10 g/day. CONCLUSIONS Male C282Y heterozygotes had significantly increased transferrin saturation values. Compound heterozygous (C282Y/H63D) subjects formed a separate category of C282Y heterozygotes in whom both iron and red cell indices were significantly increased compared with the wild-type genotype.
Query Processing, Resource Management, and Approximation ina Data Stream Management System

This paper describes our ongoing work developing the Stanford Stream Data Manager (STREAM), a system for executing continuous queries over multiple continuous data streams. The STREAM system supports a declarative query language, and it copes with high data rates and query workloads by providing approximate answers when resources are limited. This paper describes specific contributions made so far and enumerates our next steps in developing a general-purpose Data Stream Management System.
Optoelectronic systems for microwave instantaneous frequency measurement based on amplitude-phase modulation of the optical carrier

This paper considers principles of construction and methods of analysis of electro-optical probing and characterization of the Brillouin gain contour, based on using the methods of poly-harmonic probing radiation and estimation of the parameters by evaluation of envelopes of its beating frequencies at stages of searching the center frequency, the maximum gain and the width of the contour determination, as the basic characteristics of measuring conversion of temperature and strain tension/compression in a single-mode optical fiber. The purpose is to improve the metrological, technical and economic characteristics of electro-optical systems of this type.
Multidrug Resistant Acinetobacter baumannii: Risk Factors for Appearance of Imipenem Resistant Strains on Patients Formerly with Susceptible Strains

Background Multidrug resistant Acinetobacter baumannii (MDRAB) is an important nosocomial pathogen usually susceptible to carbapenems; however, growing number of imipenem resistant MDRAB (IR-MDRAB) poses further clinical challenge. The study was designed to identify the risk factors for appearance of IR-MDRAB on patients formerly with imipenem susceptible MDRAB (IS-MDRAB) and the impact on clinical outcomes. Methodology/Principal Findings A retrospective case control study was carried out for 209 consecutive episodes of IS-MDRAB infection or colonization from August 2001 to March 2005. Forty-nine (23.4%) episodes with succeeding clinical isolates of IR-MDRAB were defined as the cases and 160 (76.6%) with all subsequent clinical isolates of IS-MDRAB were defined as the controls. Quantified antimicrobial selective pressure, “time at risk”, severity of illness, comorbidity, and demographic data were incorporated for multivariate analysis, which revealed imipenem or meropenem as the only significant independent risk factor for the appearance of IR-MDRAB (adjusted OR, 1.18; 95% CI, 1.09 to 1.27). With selected cases and controls matched to exclude exogenous source of IR-MDRAB, multivariate analysis still identified carbapenem as the only independent risk factor (adjusted OR, 1.48; 95% CI, 1.14 to 1.92). Case patients had a higher crude mortality rate compared to control patients (57.1% vs. 31.3%, p = 0.001), and the mortality of case patients was associated with shorter duration of “time at risk”, i.e., faster appearance of IR-MDRAB (adjusted OR, 0.9; 95% CI, 0.83 to 0.98). Conclusions/Significance Judicious use of carbapenem with deployment of antibiotics stewardship measures is critical for reducing IR-MDRAB and the associated unfavorable outcome.
On the Composability of Design Patterns

In real applications, design patterns are almost always to be found composed with each other. It is crucial that these compositions be validated. This paper examines the notion of validity, and develops a formal method for proving or disproving it, in a context where composition is performed with formally defined operators on formally specified patterns. In particular, for validity, we require that pattern compositions preserve the features, semantics and soundness of the composed patterns. The application of the theory is demonstrated by a formal analysis of overlap-based pattern compositions and a case study of a real pattern-oriented software design.
Analyzing Performance Issues of Industrial User Interfaces: Experiences and Results

User interfaces of modern industrial automation systems are required to provide similar user experience as known from mass market consumer devices like smartphones. They need to support an increasing amount of dynamic visualizations as well as multi-touch interactions and screen gestures. However, the rich visualization frameworks that are applied and the elaborated user interfaces built on top have demanding hardware requirements, which can result in critical performance issues when run on resource-limited target platforms. In this paper we share our experiences and findings from analyzing the performance issues of a state-of-the-art user interface based on JavaFX. We describe the performance analysis approach, the tools we used for measurement and analysis, as well as insights gained into the JavaFX platform. We started with measuring and optimizing the performance of a concrete implementation of a user interface. Our results triggered immediate improvement actions, but they also led to the plan to develop of a performance model and corresponding tool support for predicting potential performance issues at design time, before the user interface is completed and deployed to the target hardware.
EC-SNe FROM SUPER-ASYMPTOTIC GIANT BRANCH PROGENITORS: THEORETICAL MODELS VERSUS OBSERVATIONS

Using a parametric approach, we determine the configuration of super-asymptotic giant branch (super-AGB) stars at the explosion as a function of the initial mass and metallicity, in order to verify if the electron-capture supernova (EC-SN) scenario involving a super-AGB star is compatible with the observations regarding SN2008ha and SN2008S. The results show that both the supernovae (SNe) can be explained in terms of EC-SNe from super-AGB progenitors having a different configuration at the collapse. The impact of these results on the interpretation of other subluminous SNe is also discussed.
Parameterized and approximation complexity of the detection pair problem in graphs

We study the complexity of the problem DETECTION PAIR. A detection pair of a graph $G$ is a pair $(W,L)$ of sets of detectors with $W\subseteq V(G)$, the watchers, and $L\subseteq V(G)$, the listeners, such that for every pair $u,v$ of vertices that are not dominated by a watcher of $W$, there is a listener of $L$ whose distances to $u$ and to $v$ are different. The goal is to minimize $|W|+|L|$. This problem generalizes the two classic problems DOMINATING SET and METRIC DIMENSION, that correspond to the restrictions $L=\emptyset$ and $W=\emptyset$, respectively. DETECTION PAIR was recently introduced by Finbow, Hartnell and Young [A. S. Finbow, B. L. Hartnell and J. R. Young. The complexity of monitoring a network with both watchers and listeners. Manuscript, 2015], who proved it to be NP-complete on trees, a surprising result given that both DOMINATING SET and METRIC DIMENSION are known to be linear-time solvable on trees. It follows from an existing reduction by Hartung and Nichterlein for METRIC DIMENSION that even on bipartite subcubic graphs of arbitrarily large girth, DETECTION PAIR is NP-hard to approximate within a sub-logarithmic factor and W[2]-hard (when parameterized by solution size). We show, using a reduction to SET COVER, that DETECTION PAIR is approximable within a factor logarithmic in the number of vertices of the input graph. Our two main results are a linear-time $2$-approximation algorithm and an FPT algorithm for DETECTION PAIR on trees.
Input uncertainty quantification: advanced tutorial

"Input uncertainty" refers to the (often unmeasured) effect of not knowing the true, correct distributions of the basic stochastic processes that drive the simulation. These include, for instance, interarrival-time and service-time distributions in queueing models; bed-occupancy distributions in health care models; distributions for the values of underlying assets in financial models; and time-to-failure and time-to-repair distributions in reliability models. When the input distributions are obtained by fitting to observed real-world data, then it is possible to quantify the impact of input uncertainty on the output results. In this tutorial we carefully define input uncertainty, describe various proposals for measuring it, contrast input uncertainty with input sensitivity, and provide and illustrate a practical approach for quantifying overall input uncertainty and the relative contribution of each input model to overall input uncertainty.
Image-Text Cross-Modal Retrieval via Modality-Specific Feature Learning

Cross-modal retrieval extends the ability of search engines to deal with the massive cross-modal data. The goal of image-text cross-modal retrieval is to search images (texts) by using text (image) queries by computing the similarities of images and texts directly. Many existing methods rely on low-level visual features and textual features for cross-modal retrieval, ignoring the characteristics existing in the raw data of different modalities. In this paper, a novel model based on modality-specific feature learning is proposed. Considering the characteristics of different modalities, the model uses two types of convolutional neural networks to map the raw data to the latent space representations for images and texts, respectively. Particularly, the convolution based network used for texts involves word embedding learning, which has been proved effective to extract meaningful textual features for text classification. In the latent space, the mapped features of images and texts form relevant and irrelevant image-text pairs, which are used by the one-vs-more learning scheme. This learning scheme can achieve ranking functionality by allowing for one relevant and more irrelevant pairs. The standard back-propagation technique is employed to update the parameters of two convolutional networks. Extensive cross-modal retrieval experiments are carried out on three challenging datasets that consist of image-document pairs or image-query click-through data from a search engine, and the results firmly demonstrate that the proposed model is much more effective.