Global Pattern Recognition Research Articles

Infrared Visual Sensing Detection Approach of Swing Arc Narrow Gap Weld Deviation Based on Outlier Data Filtering

Narrow gap arc welding interferences pose notable challenges to accurate weld deviation detection in infrared visual sensing. An outlier data filtering (ODF) approach is proposed to precisely detect weld deviation between the groove and the torch centers after eliminating the welding-induced intense disturbances in images. The ODF approach develops a global pattern recognition (GPR) based algorithm to detect the groove center, and an optimal-estimation based position consistency filtering (PCF) algorithm to locate the torch center. In addition, ODF also modifies a welding image processing procedure to prepare the groove and the wire edges for the center detections. Experimental results show that the GPR algorithm removes the simulated welding spatters of ≤ 2.48 mm diameters on the groove edge, and the PCF algorithm accurately gains the torch center with the detection error of−0.022 ~ +0.035 mm. Finally, the ODF approach realizes a precise detection of the weld deviation with the detection error of−0.107 ~ +0.079 mm, demonstrating the effectiveness of the proposed approach regardless of welding interferences.

Infrared Visual Sensing Detection of Groove Width for Swing Arc Narrow Gap Welding

To solve the current problem of poor weld formation due to groove width variation in swing arc narrow gap welding, an infrared passive visual sensing detection approach was developed in this work to measure groove width under intense welding interferences. This approach, called global pattern recognition, includes self-adaptive positioning of the ROI window, equal division thresholding and in situ dynamic clustering algorithms. Accordingly, the self-adaptive positioning method filters several of the nearest values of the arc’s highest point of the vertical coordinate and groove’s same-side edge position to determine the origin coordinates of the ROI window; the equal division thresholding algorithm then divides and processes the ROI window image to extract the groove edge and forms a raw data distribution of groove width in the data window. The in situ dynamic clustering algorithm dynamically classifies the preprocessed data in situ and finally detects the value of the groove width from the remaining true data. Experimental results show that the equal division thresholding algorithm can effectively reduce the influences of arc light and welding fume on the extraction of the groove edge. The in situ dynamic clustering algorithm can avoid disturbances from simulated welding spatters with diameters less than 2.19 mm, thus realizing the high-precision detection of the actual groove width and demonstrating stronger environmental adaptability of the proposed global pattern recognition approach.

Performing track reconstruction at the ALICE TPC using a fast Hough Transform method

The Hough Transform algorithm is a popular image analysis method that is widely used to perform global pattern recognition in images through the identification of local patterns in a suitably chosen parameter space. The algorithm can also be used to perform track reconstruction; to estimate the trajectory of individual particles when passed through the active elements of a detector volume. This paper presents a fast reconstruction method for the Time Projection Chamber (TPC) of the ALICE experiment at LHC. The method, that combines a linear Hough Transform algorithm with a fast filling of the Hough Transform parameter space, is developed within AliceO2, the new computing framework of ALICE for RUN3.

A Dorsal Visual Route Necessary for Global Form Perception: Evidence from Neuropsychological fMRI

Hierarchical models of visual processing assume that global pattern recognition is contingent on the progressive integration of local elements across larger spatial regions, operating from early through intermediate to higher-level cortical regions. Here, we present results from neuropsychological fMRI that refute such models. We report two patients, one with lesions to intermediate ventral regions and the other with damage around the intraparietal sulcus (IPS). The patient with ventral damage showed normal behavioral and BOLD responses to global Glass patterns. The patient with IPS damage was impaired in discriminating global patterns and showed a lack of significant responses to these patterns in intermediate visual regions spared by the lesion. However, this patient did show BOLD activity to translational patterns, where local element relations are important. These results suggest that activation of intermediate ventral regions is not necessary to code global patterns; instead global patterns are coded in a heterarchical fashion. High-level regions of dorsal cortex are necessary to generate global pattern coding in intermediate ventral regions; in contrast, local integration processes are not sufficient.

Effect of irradiation on the expression of DNA repair genes studied in human fibroblasts by real-time qPCR using three methods of reference gene validation

The aim of this study was to determine the effects of ionizing radiation on gene expression by using for a first time a qPCR platform specifically established for the detection of 94 DNA repair genes but also to test the robustness of these results by using three analytical methods (global pattern recognition, ΔΔCq/Normfinder and ΔΔCq/Genorm). Study was focused on these genes because DNA repair is known primarily to determine the radiation response. Six strains of normal human fibroblasts were exposed to 2Gy, and changes in gene expression were analyzed 24h thereafter. A significant change in gene expression was found for only few genes, but the genes detected were mostly different for the three analytical methods used. For GPR, a significant change was found for four genes, in contrast to the eight or nine genes when applying ΔΔCq/Genorm or ΔΔCq/Normfinder, respectively. When using all three methods, a significant change in expression was only seen for GADD45A and PCNA. These data demonstrate that (1) the genes identified to show an altered expression upon irradiation strongly depend on the analytical method applied, and that (2) overall GADD45A and PCNA appear to play a central role in this response, while no significant change is induced for any of the other DNA repair genes tested.

F09 The study on molecular changes related to energy metabolism in Huntington's disease subjects: looking for biomarkers

Huntington's disease (HD) is a neurodegenerative disorder characterised by a progressive motor and cognitive decline and psychiatric symptoms. The origin of molecular and biochemical disturbances in HD is the genetic...

Thioredoxin Interacting Protein (TXNIP) Correlates with Production of Reactive Oxygen Species (ROS) and Underlines Differences in Stress Response Gene Profile in Patients with Chronic Lymphocytic Leukemia (CLL).

Abstract 4375 IntroductionOur previous studies have focused on the role of TXNIP/ROS/TRX axis and hyperglycemia in breast cancer (Clin Cancer Res.13:3724-30, 2007). A main function of thioredoxin-interacting protein (TXNIP) is to bind and inactivate thioredoxin (TRX) leading to increased reactive oxygen species (ROS) production and apoptosis. While ROS and TRX have been examined in CLL, no studies have been performed on TXNIP levels. Based on the fact that CLL is known to have high levels of ROS compared to normal individuals and that TRX has been shown to have a protective function in CLL, we wanted to first determine if there was any correlation between TXNIP RNA and ROS production, and whether there was any relationship with TRX levels in patient plasma. MethodsVenous blood samples were obtained from the first ten consecutive patients with definite diagnosis of CLL during their routine clinic visits. Patients were selected without regard to demographics or stage or grade of disease. Prior treatment for CLL was not an exclusion criterion. Cells were purified using a Ficoll density gradient. ROS activity was measured using DCFDA by flow cytometry and reported as mean fluorescence intensity. TXNIP and TRX RNA levels were assessed by semi-quantitative PCR. Thioredoxin levels in plasma were measured using a thioredoxn-1 Elisa. Gene profiling of our patient extremes was accomplished using the Human Stress Response 96 StellARray plate and analyzed using Global Pattern Recognition software [Display omitted] ResultsOver a four week period, 10 CLL patients were seen in our clinic and participated in this study. Six out of the 10 patients were either actively being treated or had finished treatment for CLL. The rest were under observation. Three out of the 10 patients had trisomy 12 on FISH and the remaining had normal cytogenetics. We examined the levels of TXNIP RNA in our samples. The median level of TXNIP was 0.77 relative ratio (range: 0.45-1.01). The median ROS levels in our patient samples was 7108 (range 2340-10861). We found a statistically significant correlation between the level of TXNIP RNA and ROS (Fig. 1). TRX RNA levels did not significantly differ among the patients. We also measured TRX levels in the patient plasma and found a median level of 33 ng/ml (range: 18-46 ng/ml) not significantly correlating with TXNIP, TRX RNA levels or ROS levels (R2 = 0.48). Based on the correlation between TXNIP and ROS, 2 patients at either end of our spectrum (see Fig. 1, circled squares) were chosen for further analysis by targeted microarray. Patient (PT009) with the low TXNIP/ROS (currently undergoing treatment) was set as our baseline and the patient (PT005) with high TXNIP/ROS (observation only) was used as test comparison. The microarray has 96 genes involved in cellular stress response pathways. Comparing PT005 to PT009 we found of the 96 genes, 15 genes were up-regulated greater than 2-fold and 21 genes were down-regulated. Among the up-regulated genes were superoxide dismutase (SOD1), FOXO1 transcription factor, catalase (CAT) and members of the catenin family of proteins. Down-regulated genes included BAX and BCL2L1, GSK3-B, and thioredoxin reductase.In conclusion, we measured the expression of TXNIP in CLL patient samples. We found a range of TXNIP expression that robustly correlates with the level of ROS production, and is associated with differences in the stress response signature the clinical or biological relevance of which deserves further investigation. Disclosures:Turturro:Celgene: Speakers Bureau; Genentech: Speakers Bureau; Merck & Co: Research Funding.

Searching QTL by gene expression: analysis of diabesity

BackgroundRecent developments in sequence databases provide the opportunity to relate the expression pattern of genes to their genomic position, thus creating a transcriptome map. Quantitative trait loci (QTL) are phenotypically-defined chromosomal regions that contribute to allelically variant biological traits, and by overlaying QTL on the transcriptome, the search for candidate genes becomes extremely focused.ResultsWe used our novel data mining tool, ExQuest, to select genes within known diabesity QTL showing enriched expression in primary diabesity affected tissues. We then quantified transcripts in adipose, pancreas, and liver tissue from Tally Ho mice, a multigenic model for Type II diabetes (T2D), and from diabesity-resistant C57BL/6J controls. Analysis of the resulting quantitative PCR data using the Global Pattern Recognition analytical algorithm identified a number of genes whose expression is altered, and thus are novel candidates for diabesity QTL and/or pathways associated with diabesity.ConclusionTranscription-based data mining of genes in QTL-limited intervals followed by efficient quantitative PCR methods is an effective strategy for identifying genes that may contribute to complex pathophysiological processes.

Customized molecular phenotyping by quantitative gene expression and pattern recognition analysis.

Description of the molecular phenotypes of pathobiological processes in vivo is a pressing need in genomic biology. We have implemented a high-throughput real-time PCR strategy to establish quantitative expression profiles of a customized set of target genes. It enables rapid, reproducible data acquisition from limited quantities of RNA, permitting serial sampling of mouse blood during disease progression. We developed an easy to use statistical algorithm--Global Pattern Recognition--to readily identify genes whose expression has changed significantly from healthy baseline profiles. This approach provides unique molecular signatures for rheumatoid arthritis, systemic lupus erythematosus, and graft versus host disease, and can also be applied to defining the molecular phenotype of a variety of other normal and pathological processes.

Real-time 3D dose calculation and display: A tool for plan optimization

Purpose : Both human and computer optimization of treatment plans have advantages; humans are much better at global pattern recognition, and computers are much better at detailed calculations. A major impediment to human optimization of treatment plans by manipulation of beam parameters is the long time required for feedback to the operator on the effectiveness of a change in beam parameters. Our goal was to create a real-time dose calculation and display system that provides the planner with immediate (fraction of a second) feedback with displays of three-dimensional (3D) isodose surfaces, digitally reconstructed radiographs (DRRs), dose-volume histograms, and/or a figure of merit (FOM) (i.e., a single value plan score function). This will allow the experienced treatment planner to optimize a plan by adjusting beam parameters based on a direct indication of plan effectiveness, the FOM value, and to use 3D display of target, critical organs, DRRs, and isodose contours to guide changes aimed at improving the FOM value. Methods and Materials : We use computer platforms that contain easily utilized parallel processors and very tight coupling between calculation and display. We ported code running on a network of two workstations and an array of transputers to a single multiprocessor workstation. Our current high-performance graphics workstation contains four 150-MHz processors that can be readily used in a shared-memory multithreaded calculation. Results : When a 10 × 10-cm beam is moved, using an 8-mm dose grid, the full 3D dose matrix is recalculated using a Bentley—Milan-type dose calculation algorithm, and the 3D dose surface display is then updated, all in < 0.1 s. A 64 × 64-pixel DRR calculation can be performed in < 0.1 s. Other features, such as automated aperture calculation, are still required to make real-time feedback practical for clinical use. Conclusion : We demonstrate that real-time plan optimization using general pyrpose multiprocessor workstations is a practical goal. Parallel processing technology provides this capability for 3D planning systems, and when combined with objective plan ranking algorithms should prove effective for optimizing 3D conformal radiation therapy. Compared to our earlier transputer work, multiprocessor workstations are more easily programmed, making software development costs more reasonable compared with uniprocessor development costs. How the dose calculation is partitioned into parallel tasks on a multiprocessor work station can make a significant difference in performance. Shared-memory multiprocessor workstations are our first choice for future work, because they require minimum programming effort and continue to be driven to higher performance by competition in the workstation arena.

Stability of a class of nonreciprocal cellular neural networks

Cellular neural networks with an appropriate choice of templates can solve, among other things, local and global pattern recognition problems. The complete stability of these networks has been proved earlier for the symmetric (reciprocal) cases where the feedback values between the different cells within a neighborhood are the same in both directions. It is shown that at least for some interesting classes of templates, this symmetry (reciprocity) condition is in general not necessary for complete stability. Moreover, the conditions discussed are robust in the sense that they require neither precise template-value relations nor a closeness to some prescribed values. On the other hand, examples are shown of cases where violating some basic conditions would give rise to oscillations. >

Global pattern recognition in layered track chambers

We present some new ideas on pattern recognition of the layered track chambers. Our method is a modification of that of global transformations and makes valid use of not only positional, but also directional information of track segments. We apply this method to the VENUS drift chamber at TRISTAN and demonstrate that it is fast and powerful for pattern recognition of high multiplicity events with complicated e +e − jets. The reconstruction efficiency obtained is 93% for hadron events simulated by Monte Carlo program and the processing time obtained is 12 ms per track using a FACOM M382 computer. This approach is also examined using cosmic ray events.

Global methods of pattern recognition

Global methods of track finding and of parameter estimation require sufficient information to be available at a certain point on a particle trajectory. Then vector functions can be looked for such that in the space spanned by these functions each track forms a cluster of points which is well separated from the clusters of the other tracks. A clever detector lay-out can simplify this task. However, current wire chamber detectors do not provide either enough, or precise enough, measurements at points on curved trajectories to allow the application of global pattern recognition methods - improved detectors should not only provide precise coordinate measurements but also sufficiently precise measurements of the track direction.