Miracle-dz/UniFAR-FTUs huggingface dataset:
On TAG and Multicomponent TAG Parsing

The notion of mild context-sensitivity is an attempt to express the formal power needed to define the syntax of natural languages. However, all incarnati- ons of mildly context-sensitive formalisms are not equivalent. On the one hand, near the bottom of the hierarchy, we find tree adjoining grammars and, on the other hand, near the top of the hierarchy, we find multicomponent tree adjoining grammars. This paper proposes a polynomial parse time method for these two tree rewriting formalisms. This method uses range concatenation grammars as a high-level intermediate definition formalism, and yields several algorithms. Range concatenation grammar is a syntactic formalism which is both powerful, in so far as it extends linear context-free rewriting systems, and efficient, in so far as its sentences can be parsed in polynomial time. We show that any unrestricted tree adjoining grammar can be transformed into an equivalent range concatenation grammar which can be parsed in O(n6) time, and, moreover, if the input tree adjoining grammar has some restricted form, its parse time decreases to O(n5). We generalize one of these algorithms in order to process multicomponent tree adjoining grammars. We show some upper bounds on their parse times, and we introduce a hierarchy of restricted forms which can be parsed more efficiently. Our approach aims at giving both a new insight into the multicomponent adjunction mechanism and at providing a practical implementation scheme.
Application performance on the UK's new HECToR service

HECToR is the UK’s new high-end computing resource available for research funded by the UK Research Councils. The HECToR Cray XT4 system began user service in October 2007 and comprises 5,564 dual core 2.8GHz AMD Opteron processors. The results of running a number of synthetic benchmarks and popular application codes which are used by the UK academic community are presented. The synthetic benchmarks include STREAMS and MPI benchmarks. The application benchmarks include fluid dynamics, molecular dynamics, fusion, materials science and environmental science codes. The results are compared with those obtained on the UK’s HPCx service which comprises 160 IBM e-Server p575 16way SMP nodes each containing 8 dual core 1.5GHz IBM Power5 64-bit RISC chips. Where appropriate, results are also included from the HECToR Test and Development system which has a different memory structure from the main system. It is found that there is not much difference between the systems in terms of comparing similar numbers of processing cores, but HECToR is a much larger system with many more cores and a more scalable interconnect. Memory bandwidth is seen to be a bottleneck for certain applications on both systems, with HECToR more seriously affected.
The c-Myc/miR17-92/PTEN Axis Tunes PI3K Activity to Control Expression of Recombination Activating Genes in Early B Cell Development

Appropriate PI3K signals generated by the antigen receptor are essential to promote B cell development. Regulation of recombination activating gene (RAG)-1 and RAG-2 expression is one key process that is mediated by PI3K to ensure developmental progression and selection. When PI3K signals are too high or too low, expression of RAGs does not turn off and B cell development is impaired or blocked. Yet, the mechanism which tunes PI3K activity to control RAG expression during B cell development in the bone marrow is unknown. Recently we showed that a c-Myc/miR17-92/PTEN axis regulates PI3K activity for positive and negative selection of immature B cells. Here, we show that the c-Myc/miR17-92/PTEN axis tunes PI3K activity to control the expression of RAGs in proB cells. Using different genetically engineered mouse models we show that impaired function of the c-Myc/miR17-92/PTEN axis alters the PI3K/Akt/Foxo1 pathway to result in dis-regulated expression of RAG and a block in B cell development. Studies using 38c-13 B lymphoma cells, where RAGs are constitutively expressed, suggest that this regulatory effect is mediated post-translationally through Foxo1.
Power transmission line detection using an azimuth angular profile matching scheme

This paper presents high-voltage power transmission line detection with millimeter-wave (MMW) radar for the purpose of helicopter collision avoidance. In order to improve the detection, an azimuth angular profile matching (APM) scheme of the power transmission line based on the Bragg scattering phenomenon is suggested. For the evaluation of detection, we carried out a Monte Carlo simulation both at 94 GHz and 35 GHz, where a white Gaussian noise is considered as an additive noise. The results show that the detection probability with the APM at 94 GHz is much higher than that at 35 GHz and the detection performance is much improved by employing the APM.
A multivariable H/sub /spl infin// control for wind energy conversion system

This paper presents a multivariable controller for wind energy conversion system (WECS). The pitch angle and electric load are regulated to control the Wind Turbine (WT) speed, aiming to reduce mechanical stress and to improve system efficiency. The robust H/sub /spl infin// methodology is chosen to design the feedback controller, since a WECS consists of a non-linear and stochastic system. Simulation results are used to analyze the performance of proposed feedback control.
Analysis of Blind Image Quality Index

Image quality index is the measure for estimating the level of degradation present in an image. Measurement of such index is challenging in the absence of reference image. Blind image quality assessment refers to evaluating the quality of an image without the need of any reference image. The quality of an image can be considered as the contrast, sharpness, brightness and other features extracted from that particular image. Other features like Discrete Cosine Transform (DCT), Wavelet Transform and Gabor filtering can also be used to extract the quality of an image. Different algorithms are developed by researchers to solve the quality evaluation problem. These algorithms are not tested on a common platform. The algorithms that are analyzed in this thesis are Blind Image Quality Index (BIQI), Distortion Identification-based Image Verity and INtegrity Evaluation (DIIVINE), BLind Image Integrity Notator using DCT Statistics (BLIINDS) & Visual Codebook. Laboratory for Image & Video Engineering (LIVE) database which is a standard database is used to analyze the mentioned algorithms. Spearman and Pearson correlation coefficients are used for validating the algorithms. Recently Visual Codebook algorithm was proposed by Peng Ye and David Doermann. The existing Visual Codebook algorithm is optimized with respect to the number of clusters used in K-Means clustering part of algorithm. Effect of variation in patch size on the performance of algorithm is studied in this thesis and an optimum value of patch size is proposed.
Random networks in configuration space for fast path planning

In the main part of this dissertation we present a new path planning method which computes collision-free paths for robots of virtually any type moving among stationary obstacles. This method proceeds according to two phases: a preprocessing phase and a query phase. In the preprocessing phase, a probabilistic network is constructed and stored as a graph whose nodes correspond to collision-free configurations and edges to feasible paths between these configurations. These paths are computed using a fast local planner. In the query phase, any given start and goal configurations of the robot are connected to two nodes of the network; the network is then searched for a path joining these two nodes. The method is general and easy to implement. Increased efficiency can be achieved by tailoring some of its components (e.g. the local planner) to the considered robots. We apply the method to articulated robots with many degrees of freedom. Experimental results show that path planning can be done in a fraction of a second on a contemporary workstation ($\approx$150 MIPS), after relatively short preprocessing times (a few dozen to a few hundred seconds). In the second part of this dissertation, we present a new method for computing the obstacle map used in motion planning algorithms. The method computes a convolution of the workspace and the robot using the Fast Fourier Transform (FFT). It is particularly promising for workspaces with many and/or complicated obstacles. Furthermore, it is an inherently parallel method that can significantly benefit from existing experience and hardware on the FFT. In the third part of this dissertation, we consider a problem from assembly planning. In assembly planning we are interested in generating feasible sequences of motions that construct a mechanical product from its individual parts. The problem addressed is the following: given a planar assembly of polygons, decide if there is a proper subcollection of them that can be removed as a rigid body without colliding with or disturbing the other parts of the assembly. We prove that this problem is NP-complete. The result extends to several interesting variants of the problem.
Phoneme- and Word-based Language Identification of South African Languages using Lwazi

We present baseline language identification results for South African languages using the Lwazi corpus. Four different strategies to perform 11-way classification are implemented: phoneme recognition followed by language modelling (PRLM), parallel PRLM, and two analogous approaches based on word-level recognition. The optimal system uses a parallel word recognition followed by language modelling approach with trigram language models, and obtained an ID error rate of 0.418, a decision cost of 0.182, and a confusion of 2.92. West Germanic languages were easiest to identify.
Text Understanding in Lilog: Integrating Computational Linguistics and Artificial Intelligence Final Report on the IBM Germany Lilog-Project

Introducing LILOG. - Text understanding - The challenges to come. - A formalism for natural language - STUF. - The language of STUF. - Chart-parsing of STUF grammars. - The STUF workbench. - Unification-ID/LP grammars: Formalization and parsing. - A flexible parser for a Linguistic Development Environment. - Gap-Handling mechanisms in categorial grammars. - Outlines of the LEU/2 lexicology. - Morphological processing in the two-level paradigm. - Representing word meanings. - Sortal information in lexical concepts. - Incremental vocabulary extensions in text understanding systems. - Managing lexical knowledge in LEU/2. - The grammars of LILOG. - An alternative phrase structure account of symmetric coordination. - Verb order and head movement. - The Bermuda Triangle: Natural language semantics between linguistics, knowledge representation, and knowledge processing. - Presupposition, anaphora, and lexical content. - Anaphora and domain restriction. - On representing the temporal structure of texts. - The treatment of plurality in L LILOG. - The knowledge representation language LLILOG. - Knowledge packets and knowledge packet structures. - Deductive aspects of three-valued logic. - The LILOG inference engine. - Knowledge based control of the LILOG inference engine: Kinds of metaknowledge. - Attributive description formalisms . and the rest of the world. - The background knowledge of the LILOG system. - The LILOG ontology from a linguistic point of view. - A knowledge engineering environment for LILOG. - Knowledge engineering in the context of related fields of research. - LILOG-DB: Database support for knowledge based systems. - Processing of spatial expressions in LILOG. - Phenomena of localization. - Verbs of motion and position: On the optionality of the local argument. - Why a hill can't be a valley: Representing gestalt and position properties of objects with object schemata. - Object-oriented representation of depictions on the basis of cell matrices. - Integrating a generation component into a natural language understanding system. - From knowledge structures to text structures. - The formulator. - Constructing a context for LEU/2. - The text understanding system LEU/2. - The trace of building a large AI system.
VOICES OF EXPERIENCE: INTERVIEWS OF ADULT COMMUNITY BAND MEMBERS IN LAUNCESTON, TASMANIA, AUSTRALIA

From March through May 2002, the author traveled from the United States to teach at the University of Tasmania and observe a large community band program in Launceston, Tasmania. The program consists of six bands of increasing musical ability (Beginner through College) and is open to musicians of all ages and abilities. This paper is a summary of observations, a survey (n=90) and interviews (n=12) completed during the author’s stay. Adults who had learned to play their instruments in this program were interviewed to examine their motivations, their hopes, and their frustrations. The paper also describes the pedagogy used in this band program, presenting it as a model for attracting and retaining adult learners in music performance.
Automatic generation of systolic programs from nested loops

Many applications with challenging performance requirements and a high potential for parallelization can be found in the area of numerical computing. These applications, such as matrix computations, signal processing algorithms, and finite-difference methods, consist mainly of computationally intensive nested loops. While many problems in these fields have been successfully implemented on a wide variety of parallel computers, the process of programming these machines still remains tedious and ad hoc. The parallel computation model based on regularly interconnected arrays of processors with high-bandwidth neighbor-to-neighbor communication (systolic arrays) has been shown to be a highly efficient means of parallelization for this application domain. However, this efficiency is accompanied by an increased difficulty in programming arrays of processors. Among the main factors that make the programming of these machines difficult and error prone are: managing multiple threads of control in disjoint address spaces, explicitly coordinating communication between processors, and tailoring the implementation of an algorithm to machine dependent characteristics such as the number of processors and communication channels. The main contribution of this work is the reduction of the difficulty in programming systolic array computers by automatically generating programs from high-level language nested loops for a given programmable systolic array of processors. The techniques used for generating code are based on linear transformations of the same kind used for automatic synthesis of special purpose systolic arrays from algorithms with uniform dependencies. The work has been evaluated and validated on the Warp, a 10-cell programmable linear systolic array. Each Warp cell is a VLIW 10 MFLOPS processor with two communication channels to each of its neighbors. Code has been automatically generated and performance measurements have been taken for benchmark programs such as matrix multiplication, LU decomposition, QR decomposition, shortest path, transitive closure, and the Livermore loops. With the ideas and techniques introduced in this thesis, efficient parallel code can be generated and it has been shown that the performance benefits of the systolic communication programming model can be achieved from a high-level algorithm description. For instance, for the matrix computations, speedups from 7.4 to 7.9 have been obtained on 8 cells for matrices of size 120 x 120. Also, very good performance has been achieved for most of the benchmark programs, e.g., on 8 cells: 64 MFLOPS for matrix multiplication, 21 MFLOPS for LU decomposition, and 37 MFLOPS for QR decomposition.
Estructura del bienestar subjetivo mediante análisis bifactor: ¿Unidimensional o multidimensional?

Subjective Well-Being, Unidimensional or Multidimensional? Bi-Factor Analysis in a Sample of College Students In the present study the subjective well-being structure (WB) proposed by Diener (1985) was analyzed through application of a bifactor model. A total of 281 students from Córdoba, Argentina, 61.2% women, Mage=21.7, participated in the study, and were evaluated with Satisfaction with Life Scale (LS), and the Positive and Negative Affect Schedule (PA and NA, respectively). Confirmatory factor analysis was performed to evaluate two models: oblique (PA, NA and LS) and bi-factor with a general factor (GF) representing WB, and three specific ones. The bi-factor model had a better fit, although results obtained (e.g., ωh) indicate that GF only accounts for 15.9% of the variability of scores. For this reason, the model proposed by Diener (1985) has more support, which shows evidence on the multidimensionality of WB by differentiating affective and cognitive.
Specific MHC-I Peptides Are Induced Using PROTACs

Peptides presented by the class-I major histocompatibility complex (MHC-I) are important targets for immunotherapy. The identification of these peptide targets greatly facilitates the generation of T-cell-based therapeutics. Herein, we report the capability of proteolysis targeting chimera (PROTAC) compounds to induce the presentation of specific MHC class-I peptides derived from endogenous cellular proteins. Using LC-MS/MS, we identified several BET-derived MHC-I peptides induced by treatment with three BET-directed PROTAC compounds. To understand our ability to tune this process, we measured the relative rate of presentation of these peptides under varying treatment conditions using label-free mass spectrometry quantification. We found that the rate of peptide presentation reflected the rate of protein degradation, indicating a direct relationship between PROTAC treatment and peptide presentation. We additionally analyzed the effect of PROTAC treatment on the entire immunopeptidome and found many new peptides that were displayed in a PROTAC-specific fashion: we determined that these identifications map to the BET pathway, as well as, potential off-target or unique-to-PROTAC pathways. This work represents the first evidence of the use of PROTAC compounds to induce the presentation of MHC-I peptides from endogenous cellular proteins, highlighting the capability of PROTAC compounds for the discovery and generation of new targets for immunotherapy.
Comparative Analysis Workbench for Genetic Networks

To understand the nature of cellular function, it is necessary to study the behavior of genes in a holistic rather than in an individual manner because the expression and activities of genes are not isolated or independent of each other. There is lot of genetic network analysis method such as Boolean-based model, Bayesian model and Differential equation based model. However there is no agreement that which one is best, since the reliability of genetic analysis result is highly depends on the quality and the characteristics of input data. Since the experimental biologist is finally responsible for verifying the meaningfulness of the genetic network, we need a system to help biologist to compare genetic networks. Recently there is an interesting work on comparative study of the genetic networks[4]. They gave a few quality and quantitative measures to help to estimate the significance and reliability of the gene networks which one is more reliable and acceptable. In order to help these kinds of comparative study, we develop a gene regulatory network analysis and visualization tool, GENAW(GEnetic Network Analysis Workbench for microarray). GENAW accepts the expression profile of microarrays and finally produces a set of genetic network model. This system supports three well-known methods for genetic network construction (Bayesian, Boolean, Differential equation). So GENAW user enables to investigate the common or relatively different features of 3 different genetic models which were generated by a given data. Moreover GENAW provides a simple network simulation tools to efficiently investigate the regulatory relationships among genes by adjusting interaction structure and the pathway structure.
On the statistical mechanics of (un)constrained stochastic Hopfield and 'elastic' neural networks

textabstractStochastic binary Hopfield models are viewed from the angle of statistical mechanics. After an analysis of the unconstrained model using mean field theory, a similar investigation is applied to a constrained model yielding comparable general explicit formulas of the free energy. Conditions are given for which some of the free energy expressions are Lyapunov functions of the corresponding differential equations. Both stochastic models appear to coincide with a specific continuous model. Physically, the models are related to spin and Potts glass models. Also, a `complementary' free energy function of both the unconstrained and the constrained model is derived. The analysis culminates in a very general framework for analyzing constrained and unconstrained Hopfield neural networks: the stationary points of the corresponding free energy appears to coincide exactly with the set of equilibrium conditions of the corresponding continuous Hopfield neural network. Moreover, the relationship with `elastic net' algorithms is analyzed: it is proved that this class of algorithms cannot be derived from the theory of statistical mechanics (as sometimes is supposed), but should be considered as a special `penalty method', namely as one with dynamical penalty weights. We mention some experimental results and discuss implications for the use of the various models in resolving constrained optimization problems.
Molecular descriptors for chemoinformatics

Volume I: ALPHABETICAL LISTING Introduction Historical Perspective QSAR/QSPR Modeling How to Learn From This Book Users Guide Notations and Symbols Alphabetical Listing of approx. 3300 entries Greek Alphabet Entries Numerical Entries Volume II: APPENDICES, REFERENCES Full bibliography of more than 6000 references, selected from 450 journals and covering the period from the beginning of molecular descriptor research until the year 2008 Greek alphabets Acronyms Molecular structures
Concept-based Information Retrieval by using Optimal Word Sense Disambiguation

Nowadays, Word sense disambiguation (WSD) is an important technique for many NLP applications such as machine translation, grammatical analysis, content analysis and information retrieval. Information retrieval (IR) is to provide users with documents that will satisfy their information need based on the query. In the IR system, ambiguous words are damaging effect on the precision of this system. In this situation, WSD process is useful for automatically identifying the correct meaning of an ambiguous word. Therefore, this system proposes the optimal concept-based word sense disambiguation algorithm to increase the precision of the IR system about technology domain. This system provides additional semantics as conceptually related words with the help of glosses to the query words and keywords in the documents by disambiguating their meanings. In this system, various senses that are provided by concept-based WSD algorithm have been used as semantics for indexing the documents to improve performance of IR system.