Query: Simple task-specific bilingual word embeddings

Relevant passages:
Visualizing Data using t-SNE <=SEP=> We present a new technique called “t-SNE” that visualizes high-dimensional data by giving each datapoint a location in a two or three-dimensional map. The technique is a variation of Stochastic Neighbor Embedding (Hinton and Roweis, 2002) that is much easier to optimize, and produces significantly better visualizations by reducing the tendency to crowd points together in the center of the map. t-SNE is better than existing techniques at creating a single map that reveals structure at many different scales. This is particularly important for high-dimensional data that lie on several different, but related, low-dimensional manifolds, such as images of objects from multiple classes seen from multiple viewpoints. For visualizing the structure of very large datasets, we show how t-SNE can use random walks on neighborhood graphs to allow the implicit structure of all of the data to influence the way in which a subset of the data is displayed. We illustrate the performance of t-SNE on a wide variety of datasets and compare it with many other non-parametric visualization techniques, including Sammon mapping, Isomap, and Locally Linear Embedding. The visualizations produced by t-SNE are significantly better than those produced by the other techniques on almost all of the datasets.

Tailoring Continuous Word Representations for Dependency Parsing <=SEP=> Word representations have proven useful for many NLP tasks, e.g., Brown clusters as features in dependency parsing (Koo et al., 2008). In this paper, we investigate the use of continuous word representations as features for dependency parsing. We compare several popular embeddings to Brown clusters, via multiple types of features, in both news and web domains. We find that all embeddings yield significant parsing gains, including some recent ones that can be trained in a fraction of the time of others. Explicitly tailoring the representations for the task leads to further improvements. Moreover, an ensemble of all representations achieves the best results, suggesting their complementarity.

A Universal Part-of-Speech Tagset <=SEP=> To facilitate future research in unsupervised induction of syntactic structure and to standardize best-practices, we propose a tagset that consists of twelve universal part-of-speech categories. In addition to the tagset, we develop a mapping from 25 different treebank tagsets to this universal set. As a result, when combined with the original treebank data, this universal tagset and mapping produce a dataset consisting of common parts-of-speech for 22 different languages. We highlight the use of this resource via three experiments, that (1) compare tagging accuracies across languages, (2) present an unsupervised grammar induction approach that does not use gold standard part-of-speech tags, and (3) use the universal tags to transfer dependency parsers between languages, achieving state-of-the-art results.

Representation Learning: A Review and New Perspectives <=SEP=> The success of machine learning algorithms generally depends on data representation, and we hypothesize that this is because different representations can entangle and hide more or less the different explanatory factors of variation behind the data. Although specific domain knowledge can be used to help design representations, learning with generic priors can also be used, and the quest for AI is motivating the design of more powerful representation-learning algorithms implementing such priors. This paper reviews recent work in the area of unsupervised feature learning and deep learning, covering advances in probabilistic models, autoencoders, manifold learning, and deep networks. This motivates longer term unanswered questions about the appropriate objectives for learning good representations, for computing representations (i.e., inference), and the geometrical connections between representation learning, density estimation, and manifold learning.

Dependency-Based Word Embeddings <=SEP=> While continuous word embeddings are gaining popularity, current models are based solely on linear contexts. In this work, we generalize the skip-gram model with negative sampling introduced by Mikolov et al. to include arbitrary contexts. In particular, we perform experiments with dependency-based contexts, and show that they produce markedly different embeddings. The dependencybased embeddings are less topical and exhibit more functional similarity than the original skip-gram embeddings.

Intentional rounding: facilitators, benefits and barriers. <=SEP=> AIMS AND OBJECTIVES
To describe the implementation, practice and sustainability of Intentional Rounding (IR) within two diverse settings (aged care and maternity).


BACKGROUND
The profile of patients in hospitals has changed over time, generally being more severe, placing heavy demands on nurses' time. Routine non-urgent care is often provided only when there is time. IR has been found to increase both patient and staff satisfaction, also resulting in improved patient outcomes such as reduced falls and call bell use. IR is also used as a time management tool for safe and reliable provision of routine care.


METHODS
This descriptive qualitative research study comprised of three focus groups in a metropolitan hospital.


RESULTS
Fifteen nurses participated in three focus groups. Seven main themes emerged from the thematic analysis of the verbatim transcripts: implementation and maintenance, how IR works, roles and responsibilities, context and environment, benefits, barriers and legal issues.


CONCLUSION
IR was quickly incorporated into normal practice, with clinicians being able to describe the main concepts and practices. IR was seen as a management tool, facilitating accountability and continuity of management support being essential for sustainability. Clinicians reported increases in patient and staff satisfaction, and the opportunity to provide patient education. While patient type and acuity, ward layout and staff experience affected the practice of IR, the principles of IR are robust enough to allow for differences in the ward specialty and patient type. However, care must be taken when implementing IR to reduce the risk of alienating experienced staff. Incorporation of IR charts into the patient health care record is recommended.


RELEVANCE TO CLINICAL PRACTICE
Engaging all staff, encouraging ownership and stability of management are key factors in the successful implementation and maintenance of IR. IR is flexible and robust enough to accommodate different patient types and acuity.

Large-scale genome-wide association analysis of bipolar disorder identifies a new susceptibility locus near ODZ4 <=SEP=> We conducted a combined genome-wide association study (GWAS) of 7,481 individuals with bipolar disorder (cases) and 9,250 controls as part of the Psychiatric GWAS Consortium. Our replication study tested 34 SNPs in 4,496 independent cases with bipolar disorder and 42,422 independent controls and found that 18 of 34 SNPs had P < 0.05, with 31 of 34 SNPs having signals with the same direction of effect (P = 3.8 × 10−7). An analysis of all 11,974 bipolar disorder cases and 51,792 controls confirmed genome-wide significant evidence of association for CACNA1C and identified a new intronic variant in ODZ4. We identified a pathway comprised of subunits of calcium channels enriched in bipolar disorder association intervals. Finally, a combined GWAS analysis of schizophrenia and bipolar disorder yielded strong association evidence for SNPs in CACNA1C and in the region of NEK4-ITIH1-ITIH3-ITIH4. Our replication results imply that increasing sample sizes in bipolar disorder will confirm many additional loci.

Realization of a Filter with Helical Components * <=SEP=> In the VHF range, high-quality narrow-band filters with reasonable physical dimensions are extremely d8icult to realize. Excessive pass-band insertion loss accompanies filters employing lumped constant elements, and unreasonable size is a natural consequence of coaxial-resonator filters. Harmonic crystal filters are inadequate because of the unpredictable amount of spurious modes above the harmonic frequency; and hence they can only be used for very low percentage bandwidths. A solution to the above problems is provided by the use of helical resonators for high-quality filters. This paper describes the helical resonator, measurement of its Q, and coupling to the resonator. A procedure for the design and construction of a filter using helical circuits is then presented. Finally an example is given illustrating the design method, and several photographs of helical-resonator filters are shown.

Accuracy in Random Number Generation <=SEP=> The generation of continuous random variables on a digital computer encounters a problem of accuracy caused by approximations and discretization error. These in turn impose a bias on the simulation results. An ideal discrete approximation of a continuous distribution and a measure of error are proposed. Heuristic analysis of common methods for transforming uniform deviates to other continuous random variables is discussed. Comments and recommendations are made for the design of algorithms to reduce the bias and avoid overflow problems.

Low power 3–2 and 4–2 adder compressors implemented using ASTRAN <=SEP=> This paper presents two adder compressors architectures addressing high-speed and low power. Adder compressors are used to implement arithmetic circuits such as multipliers and digital signal processing units like the Fast Fourier Transform (FTT). To address the objective of high-speed and low power, it is well known that optimization efforts should be applied in all abstraction levels. In this paper are combined optimizations at logic, electrical and physical level. At the logic level, the circuit is optimized by using multiplexers instead of XOR gates to reduce delay, power and area. At the electrical level, this work presents an architecture that generate the XOR and XNOR signals simultaneously, this reduce internal glitches hence dynamic power as well. And finally at the physical level, and automatic layout generation tool (ASTRAN) is used to make the adder compressors layouts. This tool has proved to reduce power consumption and delay due to the smaller input capacitances of the complex gates generated compared to manual-designed layouts.

Review and Comparative Study of Clustering Techniques <=SEP=> Clustering is an automatic learning technique which aims at grouping a set of objects into clusters so that objects in the same clusters should be similar as possible, whereas objects in one cluster should be as dissimilar as possible from objects in other clusters. Document clustering aims to group in an unsupervised way, a given document set into clusters such that documents within each clusters are more similar between each other than those in different clusters. Cluster analysis aims to organize a collection of patterns into clusters based on similarity. This paper focuses on survey of various clustering techniques. These techniques can be divided into several categories: Partitional algorithms, Hierarchical algorithms, Density based, and comparison of various algorithm is surveyed and shows how Hierarchical Clustering can be better than other techniques.

Defect detection and identification in textile fabrics using Multi Resolution Combined Statistical and Spatial Frequency Method <=SEP=> In textile industry, reliable and accurate quality control and inspection becomes an important element. Presently, this is still accomplished by human experience, which is more time consuming and is also prone to errors. Hence automated visual inspection systems become mandatory in textile industries. This Paper presents a novel algorithm of fabric defect detection by making use of Multi Resolution Combined Statistical and Spatial Frequency Method. Defect detection consists of two phases, first is the training and next is the testing phase. In the training phase, the reference fabric images are cropped into non-overlapping sub-windows. By applying MRCSF the features of the textile fabrics are extracted and stored in the database. During the testing phase the same procedure is applied for test fabric and the features are compared with database information. Based on the comparison results, each sub-window is categorized as defective or non-defective. The classification rate obtained by the process of simulation using MATLAB was found to be 99%.

Architecture for the Internet of Things (IoT): API and Interconnect <=SEP=> The proposed architecture is structured into a secure API, a backbone, and separate device networks with standard interface to the backbone. The API decouples innovation of services and service logic from protocols and network elements. It also enables service portability between systems, i.e. a service may be allocated to end-systems or servers, with possible relocation and replication throughout its lifecycle. Ubiquitous service provisioning depends on interoperability, not only for provisioning of a standard QoS controlled IP bearer, but also for cross domain naming, security, mobility, multicast, location, routing and management, including fair compensation for utility provisioning. The proposed architecture not only includes these critical elements but also caters for multi-homing, mobile networks with dynamic membership, and third party persistent storage based on indirection.

Organophosphate Pesticide Exposure and Attention in Young Mexican-American Children: The CHAMACOS Study <=SEP=> BACKGROUND
Exposure to organophosphate (OP) pesticides, well-known neurotoxicants, has been associated with neurobehavioral deficits in children.


OBJECTIVES
We investigated whether OP exposure, as measured by urinary dialkyl phosphate (DAP) metabolites in pregnant women and their children, was associated with attention-related outcomes among Mexican-American children living in an agricultural region of California.


METHODS
Children were assessed at ages 3.5 years (n = 331) and 5 years (n = 323). Mothers completed the Child Behavior Checklist (CBCL). We administered the NEPSY-II visual attention subtest to children at 3.5 years and Conners' Kiddie Continuous Performance Test (K-CPT) at 5 years. The K-CPT yielded a standardized attention deficit/hyperactivity disorder (ADHD) Confidence Index score. Psychometricians scored behavior of the 5-year-olds during testing using the Hillside Behavior Rating Scale.


RESULTS
Prenatal DAPs (nanomoles per liter) were nonsignificantly associated with maternal report of attention problems and ADHD at age 3.5 years but were significantly related at age 5 years [CBCL attention problems: β = 0.7 points; 95% confidence interval (CI), 0.2-1.2; ADHD: β = 1.3; 95% CI, 0.4-2.1]. Prenatal DAPs were associated with scores on the K-CPT ADHD Confidence Index > 70th percentile [odds ratio (OR) = 5.1; 95% CI, 1.7-15.7] and with a composite ADHD indicator of the various measures (OR = 3.5; 95% CI, 1.1-10.7). Some outcomes exhibited evidence of effect modification by sex, with associations found only among boys. There was also limited evidence of associations between child DAPs and attention.


CONCLUSIONS
In utero DAPs and, to a lesser extent, postnatal DAPs were associated adversely with attention as assessed by maternal report, psychometrician observation, and direct assessment. These associations were somewhat stronger at 5 years than at 3.5 years and were stronger in boys.

A Survey on Query Processing and Optimization in Relational Database Management System <=SEP=> The query processer and optimizer is an important component in today’s relational database management system. This component is responsible for translating a user query, usually written in a non-procedural language like SQL – into an efficient query evaluation program that can be executed against database. In this paper, we identify many of the common issues, themes, and approaches that extend this work and the settings in which each piece of work is most appropriate. Our goal with this paper is to be a “value-add” over the existing papers on the material, providing not only a brief overview of each technique, but also a basic framework for understating the field of query processing and optimization in general.

A randomized controlled trial of postcrisis suicide prevention. <=SEP=> OBJECTIVE
This study tested the hypothesis that professionals' maintenance of long-term contact with persons who are at risk of suicide can exert a suicide-prevention influence. This influence was hypothesized to result from the development of a feeling of connectedness and to be most pertinent to high-risk individuals who refuse to remain in the health care system.


METHODS
A total of 3,005 persons hospitalized because of a depressive or suicidal state, populations known to be at risk of subsequent suicide, were contacted 30 days after discharge about follow-up treatment. A total of 843 patients who had refused ongoing care were randomly divided into two groups; persons in one group were contacted by letter at least four times a year for five years. The other group-the control group-received no further contact. A follow-up procedure identified patients who died during the five-year contact period and during the subsequent ten years. Suicide rates in the contact and no-contact groups were compared.


RESULTS
Patients in the contact group had a lower suicide rate in all five years of the study. Formal survival analyses revealed a significantly lower rate in the contact group (p=.04) for the first two years; differences in the rates gradually diminished, and by year 14 no differences between groups were observed.


CONCLUSIONS
A systematic program of contact with persons who are at risk of suicide and who refuse to remain in the health care system appears to exert a significant preventive influence for at least two years. Diminution of the frequency of contact and discontinuation of contact appear to reduce and eventually eliminate this preventive influence.

An AAL system based on IoT technologies and linked open data for elderly monitoring in smart cities <=SEP=> The average age growing of the urban population, with an increasing number of 65+ citizens, is calling for the cities to provide global services specifically geared to elderly people. In this context, collecting data from the elderly's environment and his/her habits and making them available in a structured way to third parties for analysis, is the first step towards the realization of innovative user-centric services. This paper presents a city-wide general IoT-based sensing infrastructure and a data management layer providing some REST and Linked Open Data Application Programming Interfaces (APIs) that collect and present data related to elderly people. In particular, this architecture is used by the H2020 City4Age project to help geriatricians in identifying the onset of Mild Cognitive Impairment (MCI) disease.

Bio fl oc technology in aquaculture : Bene fi cial effects and future challenges <=SEP=> 

Streaming Big Data Processing in Datacenter Clouds <=SEP=> Today, we live in a digital universe in which information and technology are not only around us but also play important roles in dictating the quality of our lives. As we delve deeper into this digital universe, we're witnessing explosive growth in the variety, velocity, and volume of data1,2 being transmitted over the Internet. A zetabyte of data passed through the Internet in the past year; IDC predicts that this digital universe will explode to an unimaginable eight Zbytes by 2015. These data are and will be generated mainly from Internet search, social media, mobile devices, the Internet of Things, business transactions, next-generation radio astronomy telescopes, high-energy physics synchrotron, and content distribution. Government and business organizations are now overflowing with data, easily aggregating to terabytes or even petabytes of information.

Integration of alternative sources of energy as current sources <=SEP=> This work proposes an integration of alternative energy sources having the different generating modules connected as current sources. These sources were configured to inject current into a common DC bus. This feature avoids current circulation among sources due to the voltage differences, reducing the stress in the individual generators. A battery bank is a system part, used as an energy accumulator for periods when there is primary energy depletion. The bus voltage is controlled by modulation of a secondary load in parallel with the main load. A DC-DC Boost converter connects each primary source to a common bus, except for the storage system that uses a DC-DC Buck-Boost converter. Finally, it is presented a mathematical analysis through simulated results to show the sources behavior and overall performance when turned into current sources.

Isolation and characterization of microsatellite loci in the black pepper, Piper nigrum L. (piperaceae) <=SEP=> The black pepper, Piper nigrum L., which originated in Índia, is the World’s most important commercial spice. Brazil has a germplasm collection of this species preserved at the Brazilian Agricultural Research Corporation (Embrapa—Eastern Amazonia) where efforts are being made to generation information on the patterns of genetic variation and develop strategies for conservation and management of black pepper. Molecular markers of the SSR type are powerful tools for the description of material preserved in genetic resources banks, due to characteristics such as high levels of polymorphism, codominance and Mendelian segregation. Given this, we developed nine microsatellite markers from an enriched library of Piper nigrum L. Twenty varieties clonal from the Brazilian germplasm collection were analyzed, and observed and expected heterozygosity values ranged over 0.11–1.00 and 0.47–0.87, respectively. The nine microsatellite loci characterized here will contribute to studies of genetic diversity and conservation of Piper nigrum L.

Global Linear Neighborhoods for Efficient Label Propagation <=SEP=> Graph-based semi-supervised learning improves classification by combining labeled and unlabeled data through label propagation. It was shown that the sparse representation of graph by weighted local neighbors provides a better similarity measure between data points for label propagation. However, selecting local neighbors can lead to disjoint components and incorrect neighbors in graph, and thus, fail to capture the underlying global structure. In this paper, we propose to learn a nonnegative low-rank graph to capture global linear neighborhoods, under the assumption that each data point can be linearly reconstructed from weighted combinations of its direct neighbors and reachable indirect neighbors. The global linear neighborhoods utilize information from both direct and indirect neighbors to preserve the global cluster structures, while the low-rank property retains a compressed representation of the graph. An efficient algorithm based on a multiplicative update rule is designed to learn a nonnegative low-rank factorization matrix minimizing the neighborhood reconstruction error. Large scale simulations and experiments on UCI datasets and high-dimensional gene expression datasets showed that label propagation based on global linear neighborhoods captures the global cluster structures better and achieved more accurate classification results.

The standard operating procedure of the DOE-JGI Microbial Genome Annotation Pipeline (MGAP v.4) <=SEP=> The DOE-JGI Microbial Genome Annotation Pipeline performs structural and functional annotation of microbial genomes that are further included into the Integrated Microbial Genome comparative analysis system. MGAP is applied to assembled nucleotide sequence datasets that are provided via the IMG submission site. Dataset submission for annotation first requires project and associated metadata description in GOLD. The MGAP sequence data processing consists of feature prediction including identification of protein-coding genes, non-coding RNAs and regulatory RNA features, as well as CRISPR elements. Structural annotation is followed by assignment of protein product names and functions.

Feature-level fusion of palmprint and palm vein for person identification based on a “Junction Point” representation <=SEP=> The issue of how to represent the palm features for effective classification is still an open problem. In this paper, we propose a novel palm representation, the "junction points" (JP) set, which is formed by the two set of line segments extracted from the registered palmprint and palm vein images respectively. Unlike the existing approaches, the JP set, containing position and orientation information, is a more compact feature that significantly reduces the storage requirement. We compare the proposed JP approach with the line-based methods on a large dataset. Experimental results show that the proposed JP approach provides a better representation and achieves lower error rate in palm verification.

Multilevel Analysis Techniques and Applications <=SEP=> The purpose of this series is to present methodological techniques to investigators and students from all functional areas of business, although individuals from other disciplines will also find the series useful. Each volume in the series will focus on a specific method The goal is to provide an understanding and working knowledge of each method with a minimum of mathematical derivations. Proposals are invited from all interested authors. Each proposal should consist of the following: (i) a brief description of the volume's focus and intended market, (ii) a table of contents with an outline of each chapter, and (iii) a curriculum vita. Materials may be sent to Dr. Contents Preface ix 1. Introduction to multilevel analysis 1 1.1. Why do we need special multilevel analysis techniques? 5 1.2. Multilevel theories 7 1.3. Models described in this book 8

Multi-Modal Fusion for Moment in Time Video Classification <=SEP=> Action recognition in videos remains a challenging problem in the machine learning community. Particularly challenging is the differing degree of intra-class variation between actions: While background information is enough to distinguish certain classes, many others are abstract and require fine-grained knowledge for discrimination. To approach this problem, in this work we evaluate different modalities on the recently published Moments in Time dataset, a collection of one million videos of short length.

Band-Notched Small Square-Ring Antenna With a Pair of T-Shaped Strips Protruded Inside the Square Ring for UWB Applications <=SEP=> A novel printed monopole antenna with constant gain over a wide bandwidth for ultra wideband applications with desired notch-band characteristic is presented. The proposed antenna consists of a square-ring radiating patch with a pair of T-shaped strips protruded inside the square ring and a coupled T-shaped strip and a ground plane with a protruded strip, which provides a wide us able fractional bandwidth of more than 130% (3.07-14.6 GHz). By using the square-ring radiating patch with a pair of T-shaped strips protruded inside it, the frequency bandstop performance is generated, and we can control its characteristics such as band-notch frequency and its bandwidth by electromagnetically adjusting coupling between a pair of T-shaped strips protruded inside the square ring. The designed antenna has a small size of 12 × 18 mm2, or about 0.15λ × 0.25λ at 4.2 GHz, while showing the band-rejection performance in the frequency band of 5.05-5.95 GHz.

Differential effects of atomoxetine on executive functioning and lexical decision in attention-deficit/hyperactivity disorder and reading disorder. <=SEP=> OBJECTIVE
The effects of a promising pharmacological treatment for attention-deficit/hyperactivity disorder (ADHD), atomoxetine, were studied on executive functions in both ADHD and reading disorder (RD) because earlier research demonstrated an overlap in executive functioning deficits in both disorders. In addition, the effects of atomoxetine were explored on lexical decision.


METHODS
Sixteen children with ADHD, 20 children with ADHD + RD, 21 children with RD, and 26 normal controls were enrolled in a randomized placebo-controlled crossover study. Children were measured on visuospatial working memory, inhibition, and lexical decision on the day of randomization and following two 28-day medication periods.


RESULTS
Children with ADHD + RD showed improved visuospatial working memory performance and, to a lesser extent, improved inhibition following atomoxetine treatment compared to placebo. No differential effects of atomoxetine were found for lexical decision in comparison to placebo. In addition, no effects of atomoxetine were demonstrated in the ADHD and RD groups.


CONCLUSION
Atomoxetine improved visuospatial working memory and to a lesser degree inhibition in children with ADHD + RD, which suggests differential developmental pathways for co-morbid ADHD + RD as compared to ADHD and RD alone.


CLINICAL TRIAL REGISTRY
B4Z-MC-LYCK, NCT00191906; http://clinicaltrials.gov/ct2/show/NCT00191906.

P300 brain computer interface: current challenges and emerging trends <=SEP=> A brain-computer interface (BCI) enables communication without movement based on brain signals measured with electroencephalography (EEG). BCIs usually rely on one of three types of signals: the P300 and other components of the event-related potential (ERP), steady state visual evoked potential (SSVEP), or event related desynchronization (ERD). Although P300 BCIs were introduced over twenty years ago, the past few years have seen a strong increase in P300 BCI research. This closed-loop BCI approach relies on the P300 and other components of the ERP, based on an oddball paradigm presented to the subject. In this paper, we overview the current status of P300 BCI technology, and then discuss new directions: paradigms for eliciting P300s; signal processing methods; applications; and hybrid BCIs. We conclude that P300 BCIs are quite promising, as several emerging directions have not yet been fully explored and could lead to improvements in bit rate, reliability, usability, and flexibility.

Event Recognition in Videos by Learning from Heterogeneous Web Sources <=SEP=> In this work, we propose to leverage a large number of loosely labeled web videos (e.g., from YouTube) and web images (e.g., from Google/Bing image search) for visual event recognition in consumer videos without requiring any labeled consumer videos. We formulate this task as a new multi-domain adaptation problem with heterogeneous sources, in which the samples from different source domains can be represented by different types of features with different dimensions (e.g., the SIFT features from web images and space-time (ST) features from web videos) while the target domain samples have all types of features. To effectively cope with the heterogeneous sources where some source domains are more relevant to the target domain, we propose a new method called Multi-domain Adaptation with Heterogeneous Sources (MDA-HS) to learn an optimal target classifier, in which we simultaneously seek the optimal weights for different source domains with different types of features as well as infer the labels of unlabeled target domain data based on multiple types of features. We solve our optimization problem by using the cutting-plane algorithm based on group based multiple kernel learning. Comprehensive experiments on two datasets demonstrate the effectiveness of MDA-HS for event recognition in consumer videos.