Learning Discriminative Bayesian Networks from High-dimensional Continuous Neuroimaging Data

Due to its causal semantics, Bayesian networks (BN) have been widely employed to discover the underlying data relationship in exploratory studies, such as brain research. Despite its success in modeling the probability distribution of variables, BN is naturally a generative model, which is not necessarily discriminative. This may cause the ignorance of subtle but critical network changes that are of investigation values across populations. In this paper, we propose to improve the discriminative power of BN models for continuous variables from two different perspectives. This brings two general discriminative learning frameworks for Gaussian Bayesian networks (GBN). In the first framework, we employ Fisher kernel to bridge the generative models of GBN and the discriminative classifiers of SVMs, and convert the GBN parameter learning to Fisher kernel learning via minimizing a generalization error bound of SVMs. In the second framework, we employ the max-margin criterion and build it directly upon GBN models to explicitly optimize the classification performance of the GBNs. The advantages and disadvantages of the two frameworks are discussed and experimentally compared. Both of them demonstrate strong power in learning discriminative parameters of GBNs for neuroimaging based brain network analysis, as well as maintaining reasonable representation capacity. The contributions of this paper also include a new Directed Acyclic Graph (DAG) constraint with theoretical guarantee to ensure the graph validity of GBN.Comment: 16 pages and 5 figures for the article (excluding appendix

A comparative study of image processing thresholding algorithms on residual oxide scale detection in stainless steel production lines

The present work is intended for residual oxide scale detection and classification through the application of image processing techniques. This is a defect that can remain in the surface of stainless steel coils after an incomplete pickling process in a production line. From a previous detailed study over reflectance of residual oxide defect, we present a comparative study of algorithms for image segmentation based on thresholding methods. In particular, two computational models based on multi-linear regression and neural networks will be proposed. A system based on conventional area camera with a special lighting was installed and fully integrated in an annealing and pickling line for model testing purposes. Finally, model approaches will be compared and evaluated their performance..Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Generating Competitive Priority Strategy in Transformer Industry

The transformer market competition in Indonesia is getting more attractive and dynamic. This encourages transformer manufacturers to improve competitiveness, such as quality, cost, timely delivery, and service. Therefore, companies need to understand customer needs and choose the right competition strategy. There are three alternative strategies to compete, cost leadership, differentiation, and focus. This research understands the customer needs and choose the right strategy to face the competition. The design of this study used survey and data collection through questionnaires. Data analysis methods using QFD and AHP combined with Focus Group Discussion (FGD) implementation. QFD analysis results in the form of the house of quality shows two major things: recommendations action for internal improvement and priority contribution value which will be the next input analysis with AHP method. The result of AHP analysis on the priority of contribution value in choosing an alternative strategy shows that the most appropriate strategy is differentiation, with the company focus on its competitive advantage. Practical implications of this research, for the management need to increase production through efficiency and cost reduction. This research develops product development theory by digging priority customer needs as one element to determine the competition strateg

Shape-based peak identification for ChIP-Seq

We present a new algorithm for the identification of bound regions from ChIP-seq experiments. Our method for identifying statistically significant peaks from read coverage is inspired by the notion of persistence in topological data analysis and provides a non-parametric approach that is robust to noise in experiments. Specifically, our method reduces the peak calling problem to the study of tree-based statistics derived from the data. We demonstrate the accuracy of our method on existing datasets, and we show that it can discover previously missed regions and can more clearly discriminate between multiple binding events. The software T-PIC (Tree shape Peak Identification for ChIP-Seq) is available at http://math.berkeley.edu/~vhower/tpic.htmlComment: 12 pages, 6 figure

Electron transport phosphorylation in rumen butyrivibrios: unprecedented ATP yield for glucose fermentation to butyrate.

From a genomic analysis of rumen butyrivibrios (Butyrivibrio and Pseudobutyrivibrio sp.), we have re-evaluated the contribution of electron transport phosphorylation (ETP) to ATP formation in this group. This group is unique in that most (76%) genomes were predicted to possess genes for both Ech and Rnf transmembrane ion pumps. These pumps act in concert with the NifJ and Bcd-Etf to form a electrochemical potential (ΔμH(+) and ΔμNa(+)), which drives ATP synthesis by ETP. Of the 62 total butyrivibrio genomes currently available from the Hungate 1000 project, all 62 were predicted to possess NifJ, which reduces oxidized ferredoxin (Fdox) during pyruvate conversion to acetyl-CoA. All 62 possessed all subunits of Bcd-Etf, which reduces Fdox and oxidizes reduced NAD during crotonyl-CoA reduction. Additionally, 61 genomes possessed all subunits of the Rnf, which generates ΔμH(+) or ΔμNa(+) from oxidation of reduced Fd (Fdred) and reduction of oxidized NAD. Further, 47 genomes possessed all six subunits of the Ech, which generates ΔμH(+) from oxidation of Fdred. For glucose fermentation to butyrate and H2, the electrochemical potential established should drive synthesis of ∼1.5 ATP by the F0F1-ATP synthase (possessed by all 62 genomes). The total yield is ∼4.5 ATP/glucose after accounting for three ATP formed by classic substrate-level phosphorylation, and it is one the highest yields for any glucose fermentation. The yield was the same when unsaturated fatty acid bonds, not H(+), served as the electron acceptor (as during biohydrogenation). Possession of both Ech and Rnf had been previously documented in only a few sulfate-reducers, was rare in other rumen prokaryotic genomes in our analysis, and may confer an energetic advantage to rumen butyrivibrios. This unique energy conservation system might enhance the butyrivibrios' ability to overcome growth inhibition by unsaturated fatty acids, as postulated herein

Climate Change Reporting: A Resource Based Perspective

Kajian ini dilakukan untuk mengkaji tahap serta faktor yang mengalakkan laporan pemanasan global di antara syarikat-syarikat yang tersenarai di Bursa Malaysia. This study investigates the extent of climate change disclosure among Malaysian public listed companies

Risk Mitigation Of Outsourcing Manufacturing Process: A Study On The Semiconductor Manufacturing Organizations In Malaysia

Penggunaan perkhidmatan pihak ketiga daripada proses pembuatan semikonduktor menjadi sebahagian daripada strategi korporat sebuah organisasi yang didorong oleh kelebihan kos dan fleksibiliti dalam ketidakpastian. Outsourcing of semiconductor manufacturing process is becoming integral part of the corporate strategy of an organization which is driven by cost advantage and flexibility during uncertainty