Search

The semiconductor manufacturing process is very complex, and it is the most important part of the semiconductor industry. In order to test whether or not wafers are functioning normally, a pass/fail test is conducted; however, time and cost needed for this testing increase as the number of chips increases. To address this, a machine learning technique is adopted and a high-performance classifier is needed to determine whether a pass/fail test is accurate or not. In this paper, a deep belief network (DBN)-based multi-classifier is proposed for fault detection prediction in the semiconductor manufacturing process. The proposed method consists of two phases: The first phase is a data pre-processing phase in which features required for semiconductor data sets are extracted and the imbalance problem is solved. The second phase is to configure the multi-DBN using selected features. A DBN classifier is created for each feature and, finally, fault detection prediction is performed. The proposed method showed excellent performance and can be used in the semiconductor manufacturing process efficiently.

To identify and quantify the contribution of the major sources for the ambient carbonaceous aerosols at a Global Atmosphere Watch (GAW) station in Korea, a receptor model, the Positive Matrix Factorization (PMF) model was applied for the one-year long measurement data. Particulate matter less than or equal to 2.5 μm in aerodynamic diameter (PM2.5) aerosols were sampled at Anmyeon Island GAW station from June 2015 to May 2016 and carbonaceous species including ~80 organic compounds were analyzed. According to the performance parameter evaluation, 5 or 7 factors were considered as optimal number of factors. It was found out that the results of 7 factors gave less contribution from the factor designated as mixed sources which we could not separate clearly. The major sources with 7 factors were identified with various analyses including chemical characteristics and air parcel movement analysis. The 7 factors with their relative contributions are; anthropogenic Secondary Organic Aerosols (SOA) (14%), biogenic SOA (15%), primary biogenic source (8%), local biomass burning (13%), transported biomass burning (16%), combustion related source (15%), and mixed sources (19%). The air parcel movement analysis results also support the identification of these factors. Thus, the Anmyeon Island GAW station has been affected by both regional and local sources for the carbonaceous aerosols.

Background We have occasionally encountered advanced lung cancer patients with disseminated carcinomatosis throughout the body and/or within the lung. This study investigated the clinical characteristics and outcomes of advanced lung adenocarcinoma patients with miliary disseminated carcinomatosis. Methods Patients with adenocarcinomas harboring epidermal growth factor receptor (EGFR) mutations who presented with miliary disseminated carcinomatosis (either intrapulmonary or distant site) were enrolled in the study. Clinical characteristics, treatment responses, and survival outcomes were collected from medical records. Results The most frequent EGFR mutation was an in-frame deletion in exon 19 (n = 44, 68.8%). Arginine substitution of leucine 858 in exon 21 and alanine substitution of glycine 719 in exon 18 were detected in 19 patients (29.7%) and one patient (1.6%), respectively. Patients with miliary disseminated carcinomatosis tended to be female and non-smokers. They expressed the E19 deletion more frequently than patients without miliary dissemination and had shorter progression-free survival times in response to EGFR tyrosine kinase inhibitors (9.7 vs. 12.8 months, P = 0.003) and poorer overall survival (15.9 vs. 29.0 months, P = 0.077). Multivariate analyses revealed that metabolic tumor volume correlated with shorter overall survival time. Conclusions Our data indicate that lung adenocarcinoma patients with miliary dissemination have relatively shorter survival times than those without miliary dissemination. The poor prognosis of patients with miliary dissemination may reflect a high tumor burden, as represented by metabolic tumor volume.

Object. Pathologic prediction of prostate cancer can be made by predicting the patient’s prostate metastasis prior to surgery based on biopsy information. Because biopsy variables associated with pathology have uncertainty regarding individual patient differences, a method for classification according to these variables is needed.Method. We propose a deep belief network and Dempster-Shafer- (DBN-DS-) based multiclassifier for the pathologic prediction of prostate cancer. The DBN-DS learns prostate-specific antigen (PSA), Gleason score, and clinical T stage variable information using three DBNs. Uncertainty regarding the predicted output was removed from the DBN and combined with information from DS to make a correct decision.Result. The new method was validated on pathology data from 6342 patients with prostate cancer. The pathology stages consisted of organ-confined disease (OCD; 3892 patients) and non-organ-confined disease (NOCD; 2453 patients). The results showed that the accuracy of the proposed DBN-DS was 81.27%, which is higher than the 64.14% of the Partin table.Conclusion. The proposed DBN-DS is more effective than other methods in predicting pathology stage. The performance is high because of the linear combination using the results of pathology-related features. The proposed method may be effective in decision support for prostate cancer treatment.

Although intermittent drainage is regarded as a key factor to reduce methane (CH4) emission from paddy soil during rice cultivation, it also could increase nitrous oxide (N2O) emission. However, the effects of intermittent drainage on CH4 and N2O emissions with different global warming potential (GWP) values have not been well examined. In the present study, the effect of a 26-day intermittent drainage from the 34th day after transplanting (DAT) to the 60th DAT on two greenhouse gas (GHG) fluxes and yield properties were compared with those of a continuous flooding system under different fertilization (NPK as control, PK, and NPK+straw) during rice cultivation. The effect of intermittent drainage on changing two GHG emissions was compared using the GWP value, calculated as CO2 equivalents by multiplying 25 and 298 to the seasonal CH4 and N2O fluxes, respectively. Under the same irrigation condition, addition of nitrogen to PK significantly increased seasonal CH4 and N2O fluxes, and addition of straw to NPK increased CH4 and N2O. Irrespective with fertilization background, the intermittent drainage significantly reduced the total GWP by ca. 41–70% as affected by the big reduction of seasonal CH4 fluxes by ca. 43–53% to that of the continuous flooding even with an increase of seasonal N2O emissions by ca. 16–43%. Rice productivity was not significantly different between the two different irrigation systems under same fertilization background. As a result, total GWP per grain yield was significantly lower in all fertilization treatments with intermittent drainage compared with continuous flooding.

Under intensive vegetable production, increased productivity is primarily considered for selecting better water management and irrigation intensity in upland soils. Soil water potential at −30 kPa (field capacity) for red pepper (Capsicum annum L.) production, which is the optimum moisture potential for plants, is recommended for Korean upland soils to maximize fruit yield; however its impact on greenhouse gas (GHG) emissions have not yet been considered. In this study, red pepper was cultivated under two soil water potentials at −30 and −50 kPa by drip irrigation control in two different textured soils (clay and sandy loams). Nitrous oxide (N2O) and methane (CH4) emissions were simultaneously investigated during the cultivation period. Results indicated N2O was the main GHG and contributed to approximate 97–9% of the total global warming potential (GWP), though the extent of its contribution varied depending on soil texture and soil moisture control with emitted CH4 being negligible throughout the investigation period. Between the treatments, soil moisture control at −50 kPa was effective in reducing the emissions of the two GHGs and also increased red pepper productivity in both clay loam and sandy loam soils. Comparing the gross GWP per unit pepper fruit yield between the treatments, maintaining soil water potential at −50 kPa by controlled irrigation led to a 50% reduction of GWP per unit pepper fruit yield. Therefore, drip irrigation control to lower soil water potential at −50 than −30 kPa is recommended to obtain high crop yield and reduce GWP per unit red pepper fruit yield for red pepper production in Korea.

Internal auditory canal (IAC) metastasis due to leptomeningeal carcinomatosis (LMC) from gastric cancer (GC) has rarely been reported. Early manifestation of symptoms, such as hearing loss, vertigo and facial paralysis, in cases of IAC metastasis due to LMC may facilitate the early detection of brain metastasis. To the best of our knowledge, the present study is the first to report IAC metastasis due to LMC in human epidermal growth factor receptor 2 (Her2)-positive GC. This study reports a case of an Her2-positive GC patient with LMC including IAC metastasis, who presented with acute sensorineural hearing loss, ipsilateral facial paralysis and vertigo during trastuzumab containing chemotherapy. The current study also discusses the early diagnosis and management of this complicated condition, demonstrating that clinical suspicion is key for a prompt diagnosis and proper management of LMC including IAC metastasis in Her2-positive GC.

The specific molecular profiles of ovarian cancer interface zones (IZ), the region between tumors and normal tissues, were evaluated using a new method involving matrix-assisted laser desorption/ionization (MALDI)-imaging mass spectrometry (IMS). We analyzed three ovarian serous carcinomas using MALDI-IMS. Principal component analysis (PCA) was used to evaluate the quality of tissue spatial features based on MALDI-IMS, and for analysis of large data sets of MALDI-IMS. Two-dimensional gel electrophoresis and fluorescence microscopy were used to verify interface-specific proteins. Unique profiles were identified for the tumors, the normal zone, and the IZ. Through MALDI analysis, two interface-specific proteins, plastin 2 and peroxiredoxin 1 (PRDX 1), were identified as differentially regulated between zones. Fluorescence microscopy revealed high expression levels of plastin 2 and PRDX 1 along the IZ of ovarian tumors. This comparative proteomics study using tissue MALDI-IMS suggested that the IZ is different from the adjacent tumor and normal zones, and that plastin 2 and PRDX 1 may be interface markers specific to ovarian tumors.

Communication data management (CDM) is an important issue in high performance distributed computing where a massive amount of data eXchange frequently occurs among geographically distributed components. In this paper, we review eXisting CDM schemes in distributed computing systems and we propose more efficient CDM schemes. Three types of quantization-based CDM schemes are proposed: the fiXed quantization-based CDM (FQ-CDM), the adaptive quantization-based CDM (AQ-CDM), and the mobility-predictive quantization-based CDM (MPQ-CDM). The FQ-CDM applies a basic theory of quantized systems to the distributed computing environment. The AQ-CDM uses a communication object clustering mechanism, which operates a pattern recognition clustering algorithm. The MPQ-CDM predicts the neXt states of communication objects by using past and current data and controls data communication among communication objects. The mobile object location monitoring system (MOLMS), based on High Level Architecture, is designed and developed to apply these CDM schemes to distributed computing. In this paper we conduct eXperiments by comparing these CDM schemes with each other on the MOLMS. The eXperimental results show that the AQ-CDM is the more effective scheme for communication message reduction and the MPQ-CDM is the more suitable scheme for mobile location error reduction.

This article reviews existing message traffic reduction schemes and proposes a dynamic multiplexing approach as an efficient message traffic reduction scheme. This approach is based on a dynamic encoding of the joint output of sender components into a single message and is applicable to a model involving distributed components moving and interacting in multidimensional space by combining with predictive interest-based quantization. This article applies this approach to a projectile/missile application with realistic multidimensional dynamics. The authors investigate the dependence of simulation accuracy and required network bandwidth on the number of active components and basic time granule. Analysis and empirical data clearly indicate the advantages of dynamic multiplexing in saving communication and computation resources in a large-scale distributed system.

A 1.8-V 2-Gb NAND flash memory has been successfully developed on a 90-nm CMOS STI process technology, resulting in a 141-mm/sup 2/ die size and a 0.044-/spl mu/m/sup 2/ effective cell. For the higher level integration, critical layers are patterned with KrF photolithography. The device has three notable differences from previous generations. 1) The cells are organized in a single (16K+512) column and 128K row array by adopting a one-sided row decoder in order to minimize the die size. 2) The bitline precharge level is set to 0.9 V in order to increase on-cell current. 3) During the program operations, the string select line, which connects the NAND cell strings to the bitlines, is biased with sub-V/sub CC/ in order to avoid program disturbance issues.

The cullin-containing ubiquitin-protein isopeptide ligases (E3s) play an important role in regulating the abundance of key proteins involved in cellular processes such as cell cycle and cytokine signaling. They have multisubunit modular structures in which substrate recognition and the catalysis of ubiquitination are carried out by distinct polypeptides. In a search for proteins involved in regulation of cullin-containing E3 ubiquitin ligases we immunopurified CUL4B-containing complex from HeLa cells and identified TIP120A as an associated protein by mass spectrometry. Immunoprecipitation of cullins revealed that all cullins tested specifically interacted with TIP120A. Reciprocal immunoaffinity purification of TIP120A confirmed the stable interaction of TIP120A with cullin family proteins. TIP120A formed a complex with CUL1 and Rbx1, but interfered with the binding of Skp1 and F-box proteins to CUL1. TIP120A greatly reduced the ubiquitination of phosphorylated IkappaBalpha by SCF(beta-TrCP) ubiquitin ligase. These results suggest that TIP120A functions as a negative regulator of SCF E3 ubiquitin ligases and may modulate other cullin ligases in a similar fashion.

A 1.8-V, 1-Gb NAND flash memory is fabricated with 0.12-/spl mu/m CMOS STI process technology. For higher integration, a 32-cell NAND structure, which enables row decoder layout in one block pitch, is applied for the first time. Resulting cell and die sizes are 0.076 /spl mu/m/sup 2/ and 129.6 mm/sup 2/, respectively. A pseudo-4-phase charge pump circuit can generate up to 20 V even under the supply voltage of 1.6 V. A newly applied cache program function and expanded page size of (2 k + 64) byte lead to program throughput of 7 MB/s. The page copy-back function is provided for on-chip garbage collection. The read throughput of 27 MB/s is achieved by simply expanding I/O width and page size. A measured disturbance free-window of 3.5 V at 1.5 V-V/sub DD/ is obtained.

Quantization is an approach to distributed logical simulation in which the value space is quantized and trajectories are represented by the crossings of a set of thresholds. This is an alternative to the common approach which discretizes the time base of a continuous trajectory to obtain a finite number of equally spaced sampled values over time. In distributed simulation, a quantizer checks for threshold crossings whenever an output event occurs and sends this value across to a receiver thereby reducing the number of messages exchanged among federates in a federation. This may increase performance in various ways such as decreasing overall execution time or allowing a larger number of entities to be simulated. Predictive quantization is a more advanced approach that sends just one bit of information instead of the actual real value size with the consequence that not only the number of messages, but also the message size, can be significantly reduced in this approach. In this paper, we present an approach to packaging individual bits into a large message packet, called multiplexed predictive quantization. We demonstrate that this approach can save significant overhead (thereby maximizing data transmission) and can reach close to 100% efficiency in the limit of large numbers of simultaneous message sources encapsulated within individual federates. We also discuss the tradeoff between message bandwidth utilization and the error incurred in the quantization. The results relate bandwidth utilization and error to quantum size for federations executing in the HLA-compliant discrete event distributed simulation environment, DEVS/HLA. The theoretical and empirical results indicate that quantization can be very scaleable due to reduced local computation demands as well as having extremely favorable network load reduction/simulation fidelity tradeoffs.

To execute complex large-scale simulation and to share geographically dispersed data assets and computing resources collaboratively, a large-scale distributed simulation is needed. To perform such distributed simulation with reasonable communication and computation resources, several message traffic reduction schemes have been proposed. In this paper, the space-based quantization scheme is introduced as a superior solution to reduce message traffic and network data transmission load. The space-based quantization is created by combining existing quantization-based filtering concepts with a spatial encounter monitoring scheme. We study the performance of space-based quantization schemes in centralized and distributed configurations operating on a test pursuer/evader federation withing the DEVS/HLA (discrete event simulation specification/high level architecture) distributed simulation environment. Empirical data illustrate the advantages of a distributed quantum-distribution scheme in reducing both message traffic and overall simulation execution time.

Signaling complexes formed on tumor necrosis factor receptor 2 (TNF-R2) contain adaptor proteins TNF-R-associated factors (TRAFs) 1 and 2, and cellular inhibitors of apoptosis (cIAPs) 1 and 2 which function as regulators of programmed cell death. TRAF2, cIAP1 and cIAP2 all have RING finger domains known to possess E3 ubiquitin ligase activity, implying that ubiquitination may play an important role in the TNF signaling pathway. In this report, we have shown that cIAP2 specifically mediated ubiquitination and proteasome-dependent degradation of TRAF1. To identify the sites for cIAP2-mediated ubiquitination of TRAF1, we used high pressure liquid chromatography coupled with tandem mass spectrometry. Lys185 and Lys193 of TRAF1 were found to be modified with ubiquitin chains. Mutation of Lys185 and Lys193 to Arg almost completely blocked cIAP2-mediated ubiquitination of TRAF1, indicating that they are the major, if not the only, sites of TRAF1 ubiquitination. Our data suggest that cIAP2 may regulate the turnover of TRAF1 by adding polyubiquitin chains on Lys185 or Lys193 following its recruitment to TNF-R signaling complexes.

The time‐frequency description of acoustic signals is a common requirement (applications include speech, sonagrams, frequency tracking, etc.), and this applies to transients and nonstationary signals (both random and nonrandom). Three time‐frequency spectra that are used are the Wigner‐Ville distribution, Priestley's evolutionary spectral density, and Kodera's modification to the moving spectrogram. This paper will present: a summary of the definitions and computation of these three different time‐frequency spectra; the modeling of acoustic signals due to propagating sources in a form allowing prediction of time‐frequency spectra; development of the interrelationships between the spectra; and theoretical and simulation results from time‐frequency spectra. Examples of the application of all three approaches will be illustrated by using frequency‐modulated signals. The signals will model sound as perceived by an observer due to a convecting acoustic source (i.e., including Doppler, range, and directivity ef...