scholarly journals An Algorithm for Intra-cell Machine Sequence Identification for Manufacturing Cells

2014 ◽  
Vol 5 ◽  
pp. 2427-2433
Author(s):  
C.R. Shiyas ◽  
V. Madhusudanan Pillai
Keyword(s):  
Manufacturing Cells ◽  
Machine Sequence ◽  
Sequence Identification

scholarly journals A machine learning approach for accurate and real-time DNA sequence identification

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Yiren Wang ◽  
Mashari Alangari ◽  
Joshua Hihath ◽  
Arindam K. Das ◽  
M. P. Anantram
Keyword(s):  
Real Time ◽  
Dna Sequence ◽  
Single Molecule ◽  
Identification Accuracy ◽  
Measuring System ◽  
Identification System ◽  
Genetic Sequencing ◽  
Sequence Identification ◽  
Tree Classifier ◽  
Single Mismatch

Abstract Background The all-electronic Single Molecule Break Junction (SMBJ) method is an emerging alternative to traditional polymerase chain reaction (PCR) techniques for genetic sequencing and identification. Existing work indicates that the current spectra recorded from SMBJ experimentations contain unique signatures to identify known sequences from a dataset. However, the spectra are typically extremely noisy due to the stochastic and complex interactions between the substrate, sample, environment, and the measuring system, necessitating hundreds or thousands of experimentations to obtain reliable and accurate results. Results This article presents a DNA sequence identification system based on the current spectra of ten short strand sequences, including a pair that differs by a single mismatch. By employing a gradient boosted tree classifier model trained on conductance histograms, we demonstrate that extremely high accuracy, ranging from approximately 96 % for molecules differing by a single mismatch to 99.5 % otherwise, is possible. Further, such accuracy metrics are achievable in near real-time with just twenty or thirty SMBJ measurements instead of hundreds or thousands. We also demonstrate that a tandem classifier architecture, where the first stage is a multiclass classifier and the second stage is a binary classifier, can be employed to boost the single mismatched pair’s identification accuracy to 99.5 %. Conclusions A monolithic classifier, or more generally, a multistage classifier with model specific parameters that depend on experimental current spectra can be used to successfully identify DNA strands.

Concurrent scheduling and layout of virtual manufacturing cells considering assembly aspects

2020 ◽  
pp. 095440542098068
Author(s):  
Kamran Forghani ◽  
S. M. T. Fatemi Ghomi ◽  
Reza Kia
Keyword(s):  
Mathematical Model ◽  
Simulated Annealing ◽  
Model Material ◽  
Virtual Manufacturing ◽  
Superior Performance ◽  
Shop Floor ◽  
Processing Route ◽  
Manufacturing Cells ◽  
Comparison Results ◽  
Virtual Manufacturing Cells

Cell formation, scheduling, and facility layout are three main decisions in designing manufacturing cells. In this paper, we address the integration of these decisions in virtual manufacturing cells considering assembly aspects and process routing. We develop a mathematical model to determine the machine cells, the layout of machines and workstations on the shop floor, the processing route of parts, and the production sequence of operations on the machines. In this mathematical model, material handling costs and cycle time are minimized. To the best of our knowledge, this is the first paper that concurrently addresses the scheduling and layout of virtual manufacturing cells with assembly aspects and so-called criteria. To effectively solve the problem, a Population-based Simulated Annealing (PSA) combined with linear programming is proposed. The practical usability of the developed model is demonstrated in a case study. Finally, instances from the literature are solved to evaluate the performance of the PSA. The comparison results showed the superior performance of the PSA in comparison with CPLEX solver and standard simulated annealing.

scholarly journals Sequence identification of cytochrome b in Plasmodium gallinaceum.

1989 ◽  
Vol 9 (9) ◽  
pp. 3614-3620 ◽  
Author(s):  
S M Aldritt ◽  
J T Joseph ◽  
D F Wirth
Keyword(s):  
Cytochrome B ◽  
Open Reading Frame ◽  
Malarial Parasite ◽  
Plasmodium Gallinaceum ◽  
Primary Transcript ◽  
Present Evidence ◽  
Reading Frame ◽  
Sequence Identification ◽  
Parasite Plasmodium ◽  
Extrachromosomal Element

We have identified a gene that encodes the polypeptide cytochrome b in the avian malarial parasite Plasmodium gallinaceum. The gene containing the open reading frame was found to be located on a 6.2-kilobase multimeric extrachromosomal element. The amino acid translation from this gene demonstrated significant similarities to cytochrome b sequences from yeast, mammal, and fungus genomes. We present evidence that the P. gallinaceum cytochrome b transcript is part of a larger primary transcript from the element that is subsequently processed. The message for P. gallinaceum cytochrome b was found to be 1.2 kilobases in size. This is the first report identifying a mitochondrial nucleic acid sequence in malaria-causing organisms and suggests that a functional cytochrome system may exist in these parasites.

scholarly journals Pectobacterium spp. Associated with Bacterial Stem Rot Syndrome of Potato in Canada

2012 ◽  
Vol 102 (10) ◽  
pp. 937-947 ◽  
Author(s):  
S. H. De Boer ◽  
X. Li ◽  
L. J. Ward
Keyword(s):  
Gene Sequence ◽  
Blackleg Disease ◽  
Chain Reaction ◽  
Biochemical Tests ◽  
Pectobacterium Atrosepticum ◽  
Physiological Characterization ◽  
Specific Polymerase Chain Reaction ◽  
Sequence Identification ◽  
Carotovorum Subsp ◽  
Polymerase Chain

Pectobacterium atrosepticum, P. carotovorum subsp. brasiliensis, P. carotovorum subsp. carotovorum, and P. wasabiae were detected in potato stems with blackleg symptoms using species- and subspecies-specific polymerase chain reaction (PCR). The tests included a new assay for P. wasabiae based on the phytase gene sequence. Identification of isolates from diseased stems by biochemical or physiological characterization, PCR, and multi-locus sequence typing (MLST) largely confirmed the PCR detection of Pectobacterium spp. in stem samples. P. atrosepticum was most commonly present but was the sole Pectobacterium sp. detected in only 52% of the diseased stems. P. wasabiae was most frequently present in combination with P. atrosepticum and was the sole Pectobacterium sp. detected in 13% of diseased stems. Pathogenicity of P. wasabiae on potato and its capacity to cause blackleg disease were demonstrated by stem inoculation and its isolation as the sole Pectobacterium sp. from field-grown diseased plants produced from inoculated seed tubers. Incidence of P. carotovorum subsp. brasiliensis was low in diseased stems, and the ability of Canadian strains to cause blackleg in plants grown from inoculated tubers was not confirmed. Canadian isolates of P. carotovorum subsp. brasiliensis differed from Brazilian isolates in diagnostic biochemical tests but conformed to the subspecies in PCR specificity and typing by MLST.

Manufacturing and Fractional Cell Formation Using a New Binary Digit Grouping Algorithm with a Pwavroid Solution Explorer Toolkit

2014 ◽  
Vol 933 ◽  
pp. 97-105
Author(s):  
Hassan Mroue ◽  
Thien My Dao
Keyword(s):  
Group Technology ◽  
Cell Formation ◽  
Optimal Solution ◽  
Binary Digit ◽  
Final Solution ◽  
Manufacturing Cells ◽  
Additional Cell ◽  
Exceptional Elements ◽  
Grouping Algorithm ◽  
Fractional Cell

A new algorithm is presented in order to search for the optimal solution of the manufacturing and fractional cell formation problem. In addition, this paper introduces a new toolkit, which is used to search for the various candidate solutions in a periodic and a waving (diversified) manner. The toolkit consists of 15 tools that play a major role in speeding up the obtainment of the final solution as well as in increasing its efficiency. The application of the binary digit grouping algorithm leads to the creation of manufacturing cells according to the concept of group technology. The nonzero entries, which remain outside the manufacturing cells, are called exceptional elements. When a lot of such elements is obtained, an additional cell called fractional (or remainder) cell may be formed; the aim of which is to reduce their number. This algorithm was tested by using illustrative examples taken from the literature and succeeded to give better or at least similar results when compared to those of other well-known algorithms.

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