Mohan Krishnamoorthy

George Mason University | GMU · Department of Computer Science

This paper reports on the development of Factory Optima, a web-based system that allows manufacturing process engineers to compose, optimise and perform trade-off analysis of manufacturing and contract service networks based on a reusable repository of performance models. Performance models formally describe process feasibility constraints and metr...

We propose an efficient one-stage stochastic optimisation algorithm for the problem of finding process controls that minimise the expectation of cost while satisfying multiple deterministic and stochastic feasibility constraints with a given high probability. The proposed algorithm is based on a series of deterministic approximations to produce a c...

In this paper, we propose an architectural design and software framework for fast development of descriptive, diagnostic, predictive, and prescriptive analytics solutions for dynamic production processes. The proposed architecture and framework will support the storage of modular, extensible, and reusable knowledge base (KB) of process performance...

Smart manufacturing requires streamlining operations and optimizing processes at a global and local level. This paper considers temporal manufacturing processes that involve physical or virtual inventories of products, parts and materials that move through a network of subprocesses. The inventory levels vary with time and are a function of the conf...

In this paper, we propose an architectural design and software framework for fast development of descriptive, diagnostic, predictive, and prescriptive analytics solutions for dynamic production processes. The proposed architecture and framework will support the storage of modular, extensible, and reusable Knowledge Base (KB) of process performance...

Smart manufacturing (SM) systems have to optimise manufacturing activities at the machine, unit or entire manufacturing facility level as well as adapting the manufacturing process on the fly as required by a variety of conditions (e.g. machine breakdowns and/or slowdowns) and unexpected variations in demands. This paper provides a framework for au...

This paper deals with stochastic temporal manufacturing processes with work-in- process inventories in which multiple products are produced from raw materials and parts. The processes may be composed of subprocesses, which, in turn may be either composite or atomic, i.e., a machine on a manufacturing floor. We assume that machines’ throughput is st...

Smart manufacturing requires streamlining operations and optimizing processes at a global and local level. This paper considers manufacturing processes that involve physical or virtual inventories of products, parts and materials, that move from machine to machine. The inventory levels vary with time and are a function of the configuration settings...

This paper is focused on decision analytics for smart manufacturing. We consider temporal manufacturing processes with stochastic throughput and inventories. We demonstrate the use of the recently proposed concept of the decision guidance analytics language to perform monitoring, analysis, planning, and execution tasks. To support these tasks we de...

Identification of the epitopes targeted by antibodies that can neutralize diverse HIV-1 strains can provide important clues for the design of a preventative vaccine. We have developed a computational approach that can identify key amino acids within the HIV-1 envelope glycoprotein that influence sensitivity to broadly cross-neutralizing antibodies....

Primer design for highly variable DNA sequences is difficult, and experimental success requires attention to many interacting constraints. The advent of next-generation sequencing methods allows the investigation of rare variants otherwise hidden deep in large populations, but requires attention to population diversity and primer localization in re...

Distributions of amino acids in each subject for representative signature patterns. (A) Each vertical bar represents a subject, and the height of the bar indicates the number of sequences sampled. The subjects are grouped according to the data set breakdown in Table 1. A solid color in a bar indicates the single amino acid found in that subject, wh...

Antibody footprint sphere scanning Holm-Bonferroni adjusted p-values for Original and Holdout data-sets. The figure shows the results of the same analysis as presented in Figure S3, except Holm-Bonferroni family-wise error rate adjusted p-values are shown instead of q-values. These adjusted p-values are stringent, supporting that cluster 437 is a s...

Cluster 437: Numbers of amino acid mismatches to the reference (acute consensus) sphere set. The figure describes the nature of the significant Holdout data signature sphere set number 437. For each of the Original and Holdout data-sets, histograms of the number of sequences with 0, 1, 2, 3, 4, 5, or 6 mismatches (the maximum observed) relative to...

Background information regarding subjects. This table summarizes basic information regarding the sample and subject, including the subject ID, the cohort that was source of the sample, the risk factor for infection and sex of the subject, Fiebig stage of infection, viral load, CD4 counts, year of sampling, country of sampling, state if known, and w...

Receiver operating characteristic curves for evaluating accuracy of amino acids to classify acute/chronic status. Threshold gradient descent regularization (TGDR) was used to evaluate the set of amino acids at certain positions that best predict whether a sequence is from an acute/early or chronic subject. One hundred random splits of the Original...

Antibody footprint sphere scanning Q-values for Original and Holdout data-sets. 226 sphere set clusters of residues on gp120 (centered around each exposed surface residue) that might be targeted by antibodies were identified, with radii selected to be the normal size of known antibody-antigen complexes. For each sphere set, Poisson regression for r...

MAb and sCD4 IC50 data and coreceptor usage of SGA clones used in our study, comparing chronic versus acute sequences, augmenting the data set first described in Keele et al (ref 1). The values given are 50% neutralization titers of monoclonal antibodies b12, 2G12, 2F5, 4E10, Z13e1, 447-52D, 447, F425, 17b, soluble CD4 (sCD4), and HIVIG, co-recepto...

All sequences generated for this study under Original Set, aligned. The first character of each sequence name indicates either the Fiebig stage at time of sampling, or C for chronic infection (see material and methods for details). The GenBank numbers are all included in the name of each sequence in the files; as there are thousands of sequences, a...

All sequences generated for this study under Holdout Set, aligned. The first character of each sequence name indicates either the Fiebig stage at time of sampling, or C for chronic infection (see material and methods for details). The GenBank numbers are all included in the name of each sequence in the files; as there are thousands of sequences, an...

All sequences generated for this study under PlasmaDonors Set, aligned. The first character of each sequence name indicates either the Fiebig stage at time of sampling, or C for chronic infection (see material and methods for details). The GenBank numbers are all included in the name of each sequence in the files; as there are thousands of sequence...

Distributions of Amino Acid Sets for Cluster 437: Sites 207, 326, 327, 422, 436, 437, 439. Sphere-sets (sets/clusters of amino acid sites within a sphere centered on a surface residue with diameter selected to fit a typical conformational antibody epitope) potentially containing antibody epitopes were evaluated using a generalized linear model fit...

Phylogenetic tree of all sequences in this study, highlighting the signature at position 12. This figure illustrates the abundance of the underlying data, the within sample diversity found in early and chronic subjects highlighting typical examples, and the basic principals of our signature identification strategy when all available sequences in th...

Difference in estimated probabilities of mismatch. For each amino acid position, a test statistic was computed to evaluate whether the frequency distribution of amino acids at the position differed between the acute/early sequences and the chronic sequences. The test statistic is the estimated probability of inter-subject amino acid mismatch for al...

Signature hypotheses raised by including all sequences per patient. Here we compared just the original data to the holdout, and these sites illustrate the complete set of sites with a p<0.2 in the original and q<0.3 in the holdout. All signatures that were identified across both data sets where chronic; in the full analysis this means that the patt...

List of functional domain HXB2 positions. Combinations of sites in these functional regions were tested for correlations with acute/early versus chronic infection. The only one that provided a combination of sites that was significant was the CCR5coR model set, the set of variable positions proximal to the conserved CCR5 binding sites; it is indica...

This part summarizes strategies to define Acute versus Chronic HIV Signature Analysis via Non-Phylogenetically-Corrected Statistical Analyses. (DOC)

Here we have identified HIV-1 B clade Envelope (Env) amino acid signatures from early in infection that may be favored at transmission, as well as patterns of recurrent mutation in chronic infection that may reflect common pathways of immune evasion. To accomplish this, we compared thousands of sequences derived by single genome amplification from...

Large databases of genetic data are often biased in their representation. Thus, selection of genetic data with desired properties, such as evolutionary representation or shared genotypes, is problematic. Selection on the basis of epidemiological variables may not achieve the desired properties. Available automated approaches to the selection of inf...