Microstructure Comparison Using Dissimilarity Metric for Additive Manufacturing of Metals

Additive Manufacturing (AM) simulations are often employed to replace the expensive experiments to study the effects of processing conditions. In process modeling, one of the key limitations is the lack of reliable validation techniques. The stochastic nature and the spatial heterogeneity of microstructures make it difficult to validate the simulated microstructures against experimentally obtained images through statistical measures (e.g. average and standard deviation of grain sizes). In this work, a validation metric is proposed that can effectively quantify the dissimilarity between two AM microstructures. The methodology involves first calculating the Angularly Resolved Chord Length Distribution (ARCLD) at representative angles and then computing the Earth Mover’s Distance (EMD) to obtain the final unitless score that is named Dissimilarity Score (DS). The efficacy of the proposed methodology was first tested on synthetic microstructures, and then on AM simulations that employ the solidification model-Cellular Automaton (CA) with IN625. Results show that DS effectively measures the dissimilarity between different microstructures. The use of DS is also extended to calibrate the CA processing simulation code to match with experimental AM images from NIST AM-Bench Challenge.

MULTI-PATCHES IRIS BASED PERSON AUTHENTICATION SYSTEM USING PARTICLE SWARM OPTIMIZATION AND FUZZY C-MEANS CLUSTERING

Locating the boundary parameters of pupil and iris and segmenting the noise free iris portion are the most challenging phases of an automated iris recognition system. In this paper, we have presented person authentication frame work which uses particle swarm optimization (PSO) to locate iris region and circular hough transform (CHT) to device the boundary parameters. To undermine the effect of the noise presented in the segmented iris region we have divided the candidate region into <i>N</i> patches and used Fuzzy c-means clustering (FCM) to classify the patches into best iris region and not so best iris region (noisy region) based on the probability density function of each patch. Weighted mean Hammimng distance is adopted to find the dissimilarity score between the two candidate irises. We have used Log-Gabor, Riesz and Taylor’s series expansion (TSE) filters and combinations of these three for iris feature extraction. To justify the feasibility of the proposed method, we experimented on the three publicly available data sets IITD, MMU v-2 and CASIA v-4 distance.

Alignment-free $d_2^*$ oligonucleotide frequency dissimilarity measure improves prediction of hosts from metagenomically-derived viral sequences

Viruses and their host genomes often share similar oligonucleotide frequency (ONF) patterns, which can be used to predict the host of a given virus by finding the host with the greatest ONF similarity. We comprehensively compared 11 ONF metrics using several k-mer lengths for predicting host taxonomy from among ∼32 000 prokaryotic genomes for 1427 virus isolate genomes whose true hosts are known. The background-subtracting measure $d_2^*$ at k = 6 gave the highest host prediction accuracy (33%, genus level) with reasonable computational times. Requiring a maximum dissimilarity score for making predictions (thresholding) and taking the consensus of the 30 most similar hosts further improved accuracy. Using a previous dataset of 820 bacteriophage and 2699 bacterial genomes, $d_2^*$ host prediction accuracies with thresholding and consensus methods (genus-level: 64%) exceeded previous Euclidian distance ONF (32%) or homology-based (22-62%) methods. When applied to metagenomically-assembled marine SUP05 viruses and the human gut virus crAssphage, $d_2^*$-based predictions overlapped (i.e. some same, some different) with the previously inferred hosts of these viruses. The extent of overlap improved when only using host genomes or metagenomic contigs from the same habitat or samples as the query viruses. The $d_2^*$ ONF method will greatly improve the characterization of novel, metagenomic viruses.

A PARTIAL MATCHING FRAMEWORK BASED ON SET EXCLUSION CRITERIA

This article introduces a partial matching framework, based on set theory criteria, for the measurement of shape similarity. The matching framework is described in an abstract way because the proposed scheme is independent of the selection of a segmentation method and feature space. This paradigm ensures the high adaptability of the algorithm and brings the implementer a wide control over the robustness, the ability to balance between selectivity and sensitivity, and the freedom to deal with more general and arbitrary image transformations required for some particular problem. A strategy to establish a descriptor set obtained from components segmented from the main shape is expounded, and two exclusion measure functions are formulated. Proofs are given to show that it is not required to match the entire descriptor sets to determine that two shapes are similar. The methodology provides a dissimilarity score that may be used for shape-based retrieval and object recognition; this is demonstrated applying the proposed approach in a cattle brand identification system.

Finnish Twins Reared Apart. IV: Smoking and Drinking Habits. A Preliminary Analysis of the Effect of Heredity and Environment

Data on alcohol use and smoking habits was available from the 1975 questionnaire of the entire cohort. Prior to pairwise analyses, the data of individuals was compared to that of age-sex matched groups of pairs reared together. The early separated twins had a higer alcohol consumption, while for smoking only slight differences were observed compared to twins reared together. Probandwise concordance rates were computed from smoking status (ever smoker/never smoker), alcohol use (user/nonuser) and “heavy” drinking (half-bottle of spirits on one occasion at least once a month). The following results were obtained in those pairs with the environmental dissimilarity score > 15:

Finnish Twins Reared Apart II: Validation of Zygosity, Environmental Dissimilarity and Weight and Height

Within the Finnish Twin Cohort of like-sexed adult twin pairs, a subgroup of pairs separated at an early age has been identified. In 165 pairs, both cotwins responded to questionnaires in 1975 and 1979. An environmental dissimilarity score was formed which consists of items on whether the twins had lived after separation in the same community, attended the same school, were on the same grade at school, how often the cotwins met, how often they met common friends and relatives and whether they attended the same clubs etc, or not. To validate the zygosity diagnosis obtained by questionnaire in 1975, those pairs whose zygosity was unknown as well as those with the least contact after separation were contacted for blood sampling (11 bloodgroups). Of 15 pairs with no zygosity diagnosis, 10 responded (1 no address,2 abroad,2 refused). Six pairs were classified MZ and 4 DZ. In 12 MZ and 8 DZ pairs undergoing bloodgroup determination, the classification of only one pair changed from DZ to MZ. The following intraclass correlations for height and weight were found:

Finnish Twins Reared Apart III: Personality Factors

This study is based on data from 165 adult twin pairs separated at 10 years or less. Information on personality factors: extraversion (E) and neuroticism (N) (EPI scale short from), life satisfaction (LS) (Allardt) and stress of daily activities (SDA) was obtained as part of the questionnaire study carried out in the entire Finnish Twin Cohort in 1975. Later in 1979 a questionnaire sent to the twins reared apart yielded a scale (range 7-30 points) measuring the environmental dissimilarities after separation (reliability 0.83). The effect of separation on personality factors by analysis of variance of individual data was studied. Sex, zygosity and age-at-separation were included in the models. The overall expalanatory rates were low (2.1-4.4%). The definitive study group was formed by selecting those pairs with a dissimilarity score greater than 15. The following intraclass correlations were obtained: