A run-to-run controller for a chemical mechanical planarization process using least squares generative adversarial networks

Achieving high processing quality for chemical mechanical planarization (CMP) in semiconductor manufacturing is difficult due to the distinct process variations associated with this method, such as drift and shift. Run-to-run control aims to maintain the targeted process quality by reducing the effect of process variations. The goal of controller learning is to infer an underlying output–input reverse mapping based on input–output samples considering the process variations. Existing controllers learn reverse mapping by minimizing the total mapping error for sample data. However, this approach often fails to generate inputs for unseen target outputs because conditional input distributions on target outputs are not captured in the learning. In this study, we propose a controller based on a least squares generative adversarial network (LSGAN) that can capture the input distributions. GANs are deep-learning architectures composed of two neural nets: a generator and a discriminator. In the proposed model, the generator attempts to produce fake input distributions that are similar to the real input distributions considering the process variation features extracted using convolutional layers, while the discriminator attempts to detect the fake distributions. Competition in this game drives both networks to improve their performance until the generated input distributions are indistinguishable from the real distributions. An experiment using the data obtained from a work-site CMP tool verified that the proposed model outperformed the comparison models in terms of control accuracy and computation time.

     

Robust pose invariant face recognition using coupled latent space discriminant analysis

We propose a novel pose-invariant face recognition approach which we call Discriminant Multiple Coupled Latent Subspace framework. It finds the sets of projection directions for different poses such that the projected images of the same subject in different poses are maximally correlated in the latent space. Discriminant analysis with artificially simulated pose errors in the latent space makes it robust to small pose errors caused due to a subject’s incorrect pose estimation. We do a comparative analysis of three popular latent space learning approaches: Partial Least Squares (PLSs), Bilinear Model (BLM) and Canonical Correlational Analysis (CCA) in the proposed coupled latent subspace framework. We experimentally demonstrate that using more than two poses simultaneously with CCA results in better performance. We report state-of-the-art results for pose-invariant face recognition on CMU PIE and FERET and comparable results on MultiPIE when using only four fiducial points for alignment and intensity features.     

The implementation of technical practices and human factors of the toyota production system in different industries

The Toyota Production System (TPS) can result in huge benefits for companies and has been widely implemented around the world. Nevertheless, most adopters emphasize only the technical practices of the TPS, but neglect the critical role of human factors in the implementation of the TPS. Therefore, this study aims at developing an integrated TPS model that fully integrates the technical elements and human elements of the TPS with Total Quality Management (TQM) practices. An empirical study was conducted to confirm the causal relationships among these constructs. In the empirical study, questionnaires were mailed and e‐mailed to 620 companies that had implemented the TPS, and 151 of the completed questionnaires were valid. These 151 respondents were divided into eight categories. The results revealed that the implementation level of each construct was significantly different in each industry. The automobile and motorcycle industries have put a great deal of effort into the application of Humanity, Human Resource Management (HRM), and TQM practices and obtained good results. Other industries, however, ignored the implementation of HRM practices. The results also revealed that the early adopters enjoyed significant benefits from the implementation of the TPS, which led high‐tech companies to start adopting TPS practices and become lean enterprises. © 2011 Wiley Periodicals, Inc.     

k-Nearest neighbor query processing algorithm for cloaking regions towards user privacy protection in location-based services

Due to the advancement of wireless internet and mobile positioning technology, the application of location-based services (LBSs) has become popular for mobile users. Since users have to send their exact locations to obtain the service, it may lead to several privacy threats. To solve this problem, a cloaking method has been proposed to blur users’ exact locations into a cloaked spatial region with a required privacy threshold (k). With the cloaked region, an LBS server can carry out a k-nearest neighbor (k-NN) search algorithm. Some recent studies have proposed methods to search k-nearest POIs while protecting a user’s privacy. However, they have at least one major problem, such as inefficiency on query processing or low precision of retrieved result. To resolve these problems, in this paper, we propose a novel k-NN query processing algorithm for a cloaking region to satisfy both requirements of fast query processing time and high precision of the retrieved result. To achieve fast query processing time, we propose a new pruning technique based on a 2D-coodinate scheme. In addition, we make use of a Voronoi diagram for retrieving the nearest POIs efficiently. To satisfy the requirement of high precision of the retrieved result, we guarantee that our k-NN query processing algorithm always contains the exact set of k nearest neighbors. Our performance analysis shows that our algorithm achieves better performance in terms of query processing time and the number of candidate POIs compared with other algorithms.     

A hybrid online-product recommendation system: Combining implicit rating-based collaborative filtering and sequential pattern analysis

Many online shopping malls in which explicit rating information is not available still have difficulty in providing recommendation services using collaborative filtering (CF) techniques for their users. Applying temporal purchase patterns derived from sequential pattern analysis (SPA) for recommendation services also often makes users unhappy with the inaccurate and biased results obtained by not considering individual preferences. The objective of this research is twofold. One is to derive implicit ratings so that CF can be applied to online transaction data even when no explicit rating information is available, and the other is to integrate CF and SPA for improving recommendation quality. Based on the results of several experiments that we conducted to compare the performance between ours and others, we contend that implicit rating can successfully replace explicit rating in CF and that the hybrid approach of CF and SPA is better than the individual ones.     

Modeling of the electrostrictive, dielectric, and piezoelectric properties of ceramic PbTiO(3)

The upper and lower limits of the electrostrictive constants, dielectric permittivities, spontaneous polarizations, and piezoelectric coefficients were calculated for ceramic PbTiO(3) from theoretical single-crystal constants. Experimental ceramic data fall between these upper and lower limits. The large piezoelectric anisotropy d(33)/d(31) of ceramic PbTiO(3 ) was shown to be related to the single-crystal PbTiO(3) electrostrictive anisotropies Q(11)/Q(12 ) and Q(44)/Q(12). The possibility of a change in sign of the ceramic d(31) coefficient due to a slight variation in the single-crystal electrostrictive anisotropies was discussed. The single-crystal and predicted ceramic hydrostatic electrostrictive constants were found to be equal. Using this result the ceramic hydrostatic g(h ) coefficient is always smaller than the single-crystal g (h), but the ceramic hydrostatic d(h) coefficient can be either larger or smaller than the single-crystal d(h) depending on the dielectric anisotropy (epsilon (11)/epsilon(33)) of the single-crystal.     

Senescence Marker Protein 30 (SMP30): A Novel Pan-Species Diagnostic Marker for the Histopathological Diagnosis of Breast Cancer in Humans and Animals

Senescence marker protein 30 (SMP30) is a cell survival factor playing an important role in vitamin C synthesis and antiapoptosis. Moreover, its cytoprotective role suggests a possibility to be related to cancer cell survival. Mammary carcinoma is a common cancer in both humans and animals. Because of its histopathological diversity, especially in the early stage, histopathological diagnosis may be complicated; therefore, a diagnostic marker is helpful for confirmation. The present study analyzed the expression pattern of SMP30 in mammary carcinoma in humans, dogs, and cats. Immunohistochemistry, immunofluorescence, and western blot analysis were used to investigate SMP30 expression patterns. The expression was specifically observed in neoplastic glandular epithelial cells. The expression increased with the malignancy of glandular epithelial cells with a highly proliferative status. However, SMP30 expression was low in normal mammary gland tissues or well-differentiated adenoma tissues. The patterns were consistently reproduced in canine primary mammary carcinoma cells and MCF-7 and MDA-MB-231 human carcinoma cell lines. This study provides useful information to understand SMP30 expression in various stages of mammary carcinoma and to suggest its utility as a pan-species diagnostic marker, thereby helping to establish strategies for diagnosing mammary carcinoma in several species.     

Identification of Cyclophilin A as a Potential Anticancer Target of Novel Nargenicin A1 Analog in AGS Gastric Cancer Cells

We recently discovered a novel nargenicin A1 analog, 23-demethyl 8,13-deoxynargenicin (compound 9), with potential anti-cancer and anti-angiogenic activities against human gastric adenocarcinoma (AGS) cells. To identify the key molecular targets of compound 9, that are responsible for its biological activities, the changes in proteome expression in AGS cells following compound 9 treatment were analyzed using two-dimensional gel electrophoresis (2-DE), followed by MALDI/TOF/MS. Analyses using chemical proteomics and western blotting revealed that compound 9 treatment significantly suppressed the expression of cyclophilin A (CypA), a member of the immunophilin family. Furthermore, compound 9 downregulated CD147-mediated mitogen-activated protein kinase (MAPK) signaling pathway, including c-Jun N-terminal kinase (JNK) and extracellular signal-regulated protein kinase 1/2 (ERK1/2) by inhibiting the expression of CD147, the cellular receptor of CypA. Notably, the responses of AGS cells to CypA knockdown were significantly correlated with the anticancer and antiangiogenic effects of compound 9. CypA siRNAs reduced the expression of CD147 and phosphorylation of JNK and ERK1/2. In addition, the suppressive effects of CypA siRNAs on proliferation, migration, invasion, and angiogenesis induction of AGS cells were associated with G2/M cell cycle arrest, caspase-mediated apoptosis, inhibition of MMP-9 and MMP-2 expression, inactivation of PI3K/AKT/mTOR pathway, and inhibition of hypoxia-inducible factor-1α (HIF-1α) and vascular endothelial growth factor (VEGF) expression. The specific interaction between compound 9 and CypA was also confirmed using the drug affinity responsive target stability (DARTS) and cellular thermal shift assay (CETSA) approaches. Moreover, in silico docking analysis revealed that the structure of compound 9 was a good fit for the cyclosporin A binding cavity of CypA. Collectively, these findings provide a novel molecular basis for compound 9-mediated suppression of gastric cancer progression through the targeting of CypA.     

Evaluation of the Effects of Developmental Trauma on Neurotransmitter Systems Using Functional Molecular Imaging

Early life stress (ELS) is strongly associated with psychiatric disorders such as anxiety, depression, and schizophrenia in adulthood. To date, biological, behavioral, and structural aspects of ELS have been studied extensively, but their functional effects remain unclear. Here, we examined NeuroPET studies of dopaminergic, glutamatergic, and serotonergic systems in ELS animal models. Maternal separation and restraint stress were used to generate single or complex developmental trauma. Body weights of animals exposed to single trauma were similar to those of control animals; however, animals exposed to complex trauma exhibited loss of body weight when compared to controls. In behavioral tests, the complex developmental trauma group exhibited a decrease in time spent in the open arm of the elevated plus-maze and an increase in immobility time in the forced swim test when compared to control animals. In NeuroPET studies, the complex trauma group displayed a reduction in brain uptake values when compared to single trauma and control groups. Of neurotransmitter systems analyzed, the rate of decrease in brain uptake was the highest in the serotonergic group. Collectively, our results indicate that developmental trauma events induce behavioral deficits, including anxiety- and depressive-like phenotypes and dysfunction in neurotransmitter systems.