The Use of Latent Semantic Indexing to Mitigate OCR Effects of Related Document Images

Due to both the widespread and multipurpose use of document images and the current availability of a high number of document images repositories, robust information retrieval mechanisms and systems have been increasingly demanded. This paper presents an approach to support the automatic generation of relationships among document images by exploiting Latent Semantic Indexing (LSI) and Optical Character Recognition (OCR). We developed the LinkDI (Linking of Document Images) service, which extracts and indexes document images content, computes its latent semantics, and defines relationships among images as hyperlinks. LinkDI was experimented with document images repositories, and its performance was evaluated by comparing the quality of the relationships created among textual documents as well as among their respective document images. Considering those same document images, we ran further experiments in order to compare the performance of LinkDI when it exploits or not the LSI technique. Experimental results showed that LSI can mitigate the effects of usual OCR misrecognition, which reinforces the feasibility of LinkDI relating OCR output with high degradation.

Knowledge acquisition by networks of interacting agents in the presence of observation errors

In this work we investigate knowledge acquisition as performed by multiple agents interacting as they infer, under the presence of observation errors, respective models of a complex system. We focus the specific case in which, at each time step, each agent takes into account its current observation as well as the average of the models of its neighbors. The agents are connected by a network of interaction of Erdos-Renyi or Barabasi-Albert type. First, we investigate situations in which one of the agents has a different probability of observation error (higher or lower). It is shown that the influence of this special agent over the quality of the models inferred by the rest of the network can be substantial, varying linearly with the respective degree of the agent with different estimation error. In case the degree of this agent is taken as a respective fitness parameter, the effect of the different estimation error is even more pronounced, becoming superlinear. To complement our analysis, we provide the analytical solution of the overall performance of the system. We also investigate the knowledge acquisition dynamic when the agents are grouped into communities. We verify that the inclusion of edges between agents (within a community) having higher probability of observation error promotes the loss of quality in the estimation of the agents in the other communities.

The impact of measurement errors in the identification of regulatory networks

Background: There are several studies in the literature depicting measurement error in gene expression data and also, several others about regulatory network models. However, only a little fraction describes a combination of measurement error in mathematical regulatory networks and shows how to identify these networks under different rates of noise. Results: This article investigates the effects of measurement error on the estimation of the parameters in regulatory networks. Simulation studies indicate that, in both time series (dependent) and non-time series (independent) data, the measurement error strongly affects the estimated parameters of the regulatory network models, biasing them as predicted by the theory. Moreover, when testing the parameters of the regulatory network models, p-values computed by ignoring the measurement error are not reliable, since the rate of false positives are not controlled under the null hypothesis. In order to overcome these problems, we present an improved version of the Ordinary Least Square estimator in independent (regression models) and dependent (autoregressive models) data when the variables are subject to noises. Moreover, measurement error estimation procedures for microarrays are also described. Simulation results also show that both corrected methods perform better than the standard ones (i.e., ignoring measurement error). The proposed methodologies are illustrated using microarray data from lung cancer patients and mouse liver time series data. Conclusions: Measurement error dangerously affects the identification of regulatory network models, thus, they must be reduced or taken into account in order to avoid erroneous conclusions. This could be one of the reasons for high biological false positive rates identified in actual regulatory network models.

Antimicrobial drug administration errors identified in Brazilian multicentric study

Medication administration errors (MAE) are the most frequent kind of medication errors. Errors with antimicrobial drugs (AD) are relevant because they may interfere inpatient safety and in the development of microbial resistance. The aim of this study is to analyze the AD errors detected in a Brazilian multicentric study of MAE. It was a devcriptive and explorotory study carried out in clinical units in five Brazilian teaching hospitals. The hospitals were investigated during 30 days. MAE were detected by observation technique. MAE were classified in categories: wrong route(WR), wrong patient(WP), wrong dose(WD) wrong time (WT) and unordered drug (UD). AD with MA E were classified by Anatomical-Therapeutical-Chemical Classification System. AD with narrow therapeutic index (NTI) wet-e identified A descriptive statistical analysis was performed using SPSS version 11.5 software. A total of 1500 errors were observed, 277 (18.5%) of them were error with AD. The hopes of AD error were: WT87.7%, QD 6.9%, WR 1.5%, UD 3.2% and WP 0.7%. The number of AD found was 36. The mostly ATC class were fluoroquinolones 13.9%, combinations of penicillin 13.9%, macrolides 8.3% and third-generation cephalosporines 5.6%. The parenteral drug dosage form was associated with 55.6% of AD. 16.7% of AD were NTI. 47.4% of WD and 21.8% WT were with NTI drugs. This study shows that these errors should be considered potential areas for improvement in the medication process and patient safety plus there is requirement to develop rational drug use of AD.

Offline Detection, Identification, and Correction of Branch Parameter Errors Based on Several Measurement Snapshots

This paper proposes a three-stage offline approach to detect, identify, and correct series and shunt branch parameter errors. In Stage 1 the branches suspected of having parameter errors are identified through an Identification Index (II). The II of a branch is the ratio between the number of measurements adjacent to that branch, whose normalized residuals are higher than a specified threshold value, and the total number of measurements adjacent to that branch. Using several measurement snapshots, in Stage 2 the suspicious parameters are estimated, in a simultaneous multiple-state-and-parameter estimation, via an augmented state and parameter estimator which increases the V - theta state vector for the inclusion of suspicious parameters. Stage 3 enables the validation of the estimation obtained in Stage 2, and is performed via a conventional weighted least squares estimator. Several simulation results (with IEEE bus systems) have demonstrated the reliability of the proposed approach to deal with single and multiple parameter errors in adjacent and non-adjacent branches, as well as in parallel transmission lines with series compensation. Finally the proposed approach is confirmed on tests performed on the Hydro-Quebec TransEnergie network.

Robot measuring form errors

This work presents an automated system for the measurement of form errors of mechanical components using an industrial robot. A three-probe error separation technique was employed to allow decoupling between the measured form error and errors introduced by the robotic system. A mathematical model of the measuring system was developed to provide inspection results by means of the solution of a system of linear equations. A new self-calibration procedure, which employs redundant data from several runs, minimizes the influence of probes zero-adjustment on the final result. Experimental tests applied to the measurement of straightness errors of mechanical components were accomplished and demonstrated the effectiveness of the employed methodology. (C) 2007 Elsevier Ltd. All rights reserved.

A Procedure for Semantic Querying in the Adaptive Formalism

This paper contains a new proposal for the definition of the fundamental operation of query under the Adaptive Formalism, one capable of locating functional nuclei from descriptions of their semantics. To demonstrate the method`s applicability, an implementation of the query procedure constrained to a specific class of devices is shown, and its asymptotic computational complexity is discussed.

Diagnostic errors and repetitive sequential classifications in on-line process control by attributes

The procedure of on-line process control by attributes, known as Taguchi`s on-line process control, consists of inspecting the mth item (a single item) at every m produced items and deciding, at each inspection, whether the fraction of conforming items was reduced or not. If the inspected item is nonconforming, the production is stopped for adjustment. As the inspection system can be subject to diagnosis errors, one develops a probabilistic model that classifies repeatedly the examined item until a conforming or b non-conforming classification is observed. The first event that occurs (a conforming classifications or b non-conforming classifications) determines the final classification of the examined item. Proprieties of an ergodic Markov chain were used to get the expression of average cost of the system of control, which can be optimized by three parameters: the sampling interval of the inspections (m); the number of repeated conforming classifications (a); and the number of repeated non-conforming classifications (b). The optimum design is compared with two alternative approaches: the first one consists of a simple preventive policy. The production system is adjusted at every n produced items (no inspection is performed). The second classifies the examined item repeatedly r (fixed) times and considers it conforming if most classification results are conforming. Results indicate that the current proposal performs better than the procedure that fixes the number of repeated classifications and classifies the examined item as conforming if most classifications were conforming. On the other hand, the preventive policy can be averagely the most economical alternative rather than those ones that require inspection depending on the degree of errors and costs. A numerical example illustrates the proposed procedure. (C) 2009 Elsevier B. V. All rights reserved.

Effects of the preventive and corrective adjustments in economical designs for online process control for attributes with misclassification errors

The procedure for online process control by attributes consists of inspecting a single item at every m produced items. It is decided on the basis of the inspection result whether the process is in-control (the conforming fraction is stable) or out-of-control (the conforming fraction is decreased, for example). Most articles about online process control have cited the stoppage of the production process for an adjustment when the inspected item is non-conforming (then the production is restarted in-control, here denominated as corrective adjustment). Moreover, the articles related to this subject do not present semi-economical designs (which may yield high quantities of non-conforming items), as they do not include a policy of preventive adjustments (in such case no item is inspected), which can be more economical, mainly if the inspected item can be misclassified. In this article, the possibility of preventive or corrective adjustments in the process is decided at every m produced item. If a preventive adjustment is decided upon, then no item is inspected. On the contrary, the m-th item is inspected; if it conforms, the production goes on, otherwise, an adjustment takes place and the process restarts in-control. This approach is economically feasible for some practical situations and the parameters of the proposed procedure are determined minimizing an average cost function subject to some statistical restrictions (for example, to assure a minimal levelfixed in advanceof conforming items in the production process). Numerical examples illustrate the proposal.

Coarse-grid higher order finite-difference time-domain algorithm with low dispersion errors

Higher order (2,4) FDTD schemes used for numerical solutions of Maxwell`s equations are focused on diminishing the truncation errors caused by the Taylor series expansion of the spatial derivatives. These schemes use a larger computational stencil, which generally makes use of the two constant coefficients, C-1 and C-2, for the four-point central-difference operators. In this paper we propose a novel way to diminish these truncation errors, in order to obtain more accurate numerical solutions of Maxwell`s equations. For such purpose, we present a method to individually optimize the pair of coefficients, C-1 and C-2, based on any desired grid size resolution and size of time step. Particularly, we are interested in using coarser grid discretizations to be able to simulate electrically large domains. The results of our optimization algorithm show a significant reduction in dispersion error and numerical anisotropy for all modeled grid size resolutions. Numerical simulations of free-space propagation verifies the very promising theoretical results. The model is also shown to perform well in more complex, realistic scenarios.

Episodic and semantic memory in children with mesial temporal sclerosis

The aim of this study was to analyze semantic and episodic memory deficits in children with mesial temporal sclerosis (MTS) and their correlation with clinical epilepsy variables. For this purpose, 19 consecutive children and adolescents with MTS (8 to 16 years old) were evaluated and their performance on five episodic memory tests (short- and long-term memory and learning) and four semantic memory tests was compared with that of 28 healthy volunteers. Patients performed worse on tests of immediate and delayed verbal episodic memory, visual episodic memory, verbal and visual learning, mental scanning for semantic clues, object naming, word definition, and repetition of sentences. Clinical variables such as early age at seizure onset, severity of epilepsy, and polytherapy impaired distinct types of memory. These data confirm that children with MTS have episodic memory deficits and add new information on semantic memory. The data also demonstrate that clinical variables contribute differently to episodic and semantic memory performance. (C) 2011 Elsevier Inc. All rights reserved.

Semantic memory impairment in temporal lobe epilepsy associated with hippociampal sclerosis

Episodic memory impairment is a well-recognized feature of mesial temporal lobe epilepsy. Semantic memory has received much less attention in this patient population. In this study, semantic memory aspects (word-picture matching, word definition, confrontation and responsive naming, and word list generation) in 19 patients with left and right temporal lobe epilepsy secondary to mesial temporal sclerosis (MTS) were compared with those of normal controls. Patients with LMTS showed impaired performance in word definition (compared to controls and RMTS) and in responsive naming (compared to controls). RMTS and LMTS patients performed worse than controls in word-picture matching. Both patients with left and right mesial temporal lobe epilepsy performed worse than controls in word list generation and in confrontation naming tests. Attentional-executive dysfunction may have contributed to these deficits. We conclude that patients with left and right NITS display impaired aspects of semantic knowledge. A better understanding of semantic processing difficulties in these patients will provide better insight into the difficulties with activities of daily living in this patient population. (C) 2007 Elsevier Inc. All rights reserved.

Transcriptional Errors in Human Immunodeficiency Virus Type 1 Generate Targets for T-Cell Responses

We measured T-cell responses to human immunodeficiency virus type 1 (HIV-1) cryptic epitopes encoded by regions of the viral genome not normally translated into viral proteins. T-cell responses to cryptic epitopes and to regions normally spliced out of the HIV-1 viral proteins Rev and Tat were detected in HIV-1-infected subjects.

From medical librarian to informacionist: semantic traces of their profiles and areas of performance

This literature review retakes the discussion of the profiles and competences of the information area professional, specifically, in the health field. Therefore, the aim here is to outline the new fields of performance for the informationist and the profiles required in the health context.

Production of atypical category exemplars in patients with schizophrenia

Previous studies have revealed semantic memory impairments in patients with schizophrenia, and suggested that certain of these impairments were related to thought disorganization. One explanation offered for this is a broadening of the boundaries of semantic categories in schizophrenia. We selected 16 semantic categories, and required a sample of 41 schizophrenia patients and 43 healthy control subjects to produce one exemplar from each category. The typicality of the subjects` responses was rated. The exemplars produced by the patients were on average less typical than those produced by the healthy controls. No significant association between typicality of the response and thought disorganization was revealed in the patient sample. Affective flattening, alogia, and anhedonia were significantly and inversely associated with the typicality score, that is, higher ratings of these symptoms were associated with more typical responses. Our results suggest that a broadening of semantic category boundaries is observed in patients with schizophrenia, but is unrelated to thought disorganization. This semantic abnormality is not a feature of the patients with high ratings of certain negative symptoms. (JINS, 2010, 16, 822-828.)