Mixed-type Patterns Research Articles

Detection and Recognition of Mixed-Type Defect Patterns in Wafer Bin Maps via Tensor Voting

Spatial defect patterns on semiconductor wafer bin maps can provide valuable information on the root causes of process abnormalities. Thus, the identification of these patterns is important for quality management and yield improvement. To date, most research has focused on the case of a single defect pattern. The recognition of mixed-type patterns is challenging as the patterns need to be separated into clusters and each cluster classified as a predefined type of defect pattern. In this study, we propose a novel method for mixed-type defect pattern detection and recognition in wafer bin maps. We separate mixed-type defect patterns into clusters using tensor voting. Marching algorithms are then developed to extract region and curve patterns based on the structural saliency information of the voting process. Our method is inherently robust against noise and sufficiently flexible to deal with complex defect patterns. The results obtained using real and simulated data demonstrate the effectiveness of the proposed method in the detection and recognition of both single and mixed-type defect patterns.

Assessment of MDA and 8-OHdG expressions in ovine pulmonary adenocarcinomas by immunohistochemical and immunofluorescence methods

This study aimed to reveal the presence of reactive oxygen species (ROS)-induced lipid peroxidation and DNA damage in ovine pulmonary adenocarcinomas (OPA) by evaluating malondialdehyde (MDA) and 8-hydroxy-2-deoxyguanosine (8-OHdG) expressions by immunohistochemical and immunofluorescence methods. Lung tissue samples were collected from 26 sheep brought to the Pathology Department for routine diagnosis. Lung tissues were fixed in 10% neutral buffered formalin, following routine procedures tissues were stained with hematoxylin and eosin. Avidin-Biotin Peroxidase method was used as immunohistochemical staining. Indirect immunofluorescence method was applied to the sections. Tumoral cells showed acinar, papillary or mixed type patterns. Only 2 of 20 cases metastasized to regional lymph nodes. All OPAs were immune positive for Jaagsiekte Sheep Retrovirus Capsid Protein (JSRV CA), MDA and 8-OHdG. The control group was negative for JSRV CA, MDA and 8-OHdG expressions. Malondialdehyde and 8-OHdG immune positive cells were statistically increased in the OPA group compared to the control group. In conclusion, our results demonstrate that higher MDA and 8-OHdG expressions in sheep with OPA suggest that OPA may be closely related to lipid peroxidation and oxidative DNA damage.

Spatiotemporal instabilities and pattern formation in systems of diffusively coupled Izhikevich neurons

Neurons are often connected, spatially and temporally, in phenomenal ways that promote wave propagation. Therefore, it is essential to analyze the emergent spatiotemporal patterns to understand the working mechanism of brain activity, especially in cortical areas. Here, we present an explicit mathematical analysis, corroborated by numerical results, to identify and investigate the spatiotemporal, non-uniform, patterns that emerge due to instability in an extended homogeneous 2D spatial domain, using the excitable Izhikevich neuron model. We examine diffusive instability and perform bifurcation and fixed-point analyses to characterize the patterns and their stability. Then, we derive analytically the amplitude equations that establish the activities of reaction-diffusion structures. We report on the emergence of diverse spatial structures including hexagonal and mixed-type patterns by providing a systematic mathematical approach, including variations in correlated oscillations, pattern variations and amplitude fluctuations. Our work shows that the emergence of spatiotemporal behavior, commonly found in excitable systems, has the potential to contribute significantly to the study of diffusively-coupled biophysical systems at large.

Novel method for detection of mixed-type defect patterns in wafer maps based on a single shot detector algorithm

In semiconductor manufacturing, detecting defect patterns is important because they are directly related to the root causes of failures in the wafer process. The rapid advancement of the integrated circuit technology has recently led to more frequent occurrences of mixed-type defect patterns, wherein two or more defect patterns simultaneously occur in a wafer bin map. The detection of these mixed patterns is more difficult than that of single patterns. To detect these mixed patterns, binary relevance approaches based on convolutional neural networks have been proposed. However, as the manufacturing process has been advanced and integrated, various failure types are newly detected, thus the number of single models can be continuously increased following the diversification of defect types. Therefore, we propose an effective framework for detecting mixed-type patterns in which a simple single model, called the single shot detector, is employed. By applying the proposed model to the WM-811K dataset, we show that our framework outperforms existing CNN-based methods and also provides defect location information.

A Novel DBSCAN-Based Defect Pattern Detection and Classification Framework for Wafer Bin Map

Defective die on a wafer map tend to cluster in distinguishable patterns, and such defect patterns can provide crucial information to identify equipment problems or process failures in the semiconductor manufacturing. Therefore, it is important to accurately and efficiently classify the defect patterns. In this paper, we propose a novel clustering-based defect pattern detection and classification framework for wafer bin map (WBM). The proposed framework has many advantages. Outlier detection and defect cluster pattern extraction can be done at the same time; arbitrarily shaped cluster patterns can be detected; and there is no need to specify the number of clusters in advance. Based on WBM property, the parameters used in the clustering algorithm are fixed so that parameter sensitivity can be avoided. Since the defect patterns are classified based on extracted features, no labeled data and no supervised classification training are needed and single-type patterns as well as mixed-type patterns can be found. Extensive experiments conducted on a real-world WM-811K dataset has shown the superiority of proposed framework. The proposed framework can also be used in a big data environment to accelerate performance.

Human brain monoamine oxidase type B: mechanism of deamination as probed by steady-state methods.

Recently, evidence has been published which suggests that [Husain, M., Edmondson, D. E., & Singer, T.P. (1982) Biochemistry 21, 595-600] monoamine oxidase [amine:oxygen oxidoreductase (MAO), EC 1.4.3.4] deaminates phenylethylamine and benzylamine via two distinct kinetic pathways which involve either binary or ternary complex formation, respectively. These conclusions were drawn largely from stopped-flow kinetic analysis performed on purified enzyme removed from its native membrane and in the presence of the inhibitory detergent Triton X-100. In this study, d-amphetamine and alternative substrates were used as steady-state probes of the kinetics of deamination by the B form of human brain MAO using native membrane-bound enzyme. Initial velocity studies showed mixed-type patterns for amphetamine inhibition of phenylethylamine, tryptamine, and tyramine when either amine or oxygen was the varied substrate. Slope and intercept vs. amphetamine concentration replots were linear in all cases except for phenylethylamine (hyperbolic); Ki values obtained from linear replots of slope or intercept values were comparable. In contrast, amphetamine was a competitive inhibitor of benzylamine deamination when amine concentration was varied and uncompetitive when oxygen concentration was varied; slope and intercept replots were linear for both. When benzylamine was the alternative substrate inhibitor and tyramine and tryptamine deamination was measured, mixed-type inhibition patterns were obtained when either amine or oxygen concentration was varied; replots of slope and intercept were linear in all cases.(ABSTRACT TRUNCATED AT 250 WORDS)