25 research outputs found
Design of experiments on a semiconductor plasma ashing process : methods and analysis
No full textThesis: M. Eng. in Advanced Manufacturing and Design, Massachusetts Institute of Technology, Department of Mechanical Engineering, 2016.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Cataloged from student-submitted PDF version of thesis.Includes bibliographical references (pages 115-117).Characterizing and controlling process variations in semiconductor manufacturing processes is crucial to ensure the extremely low defect and scrap rates that are needed for semiconductor manufacturing companies to maximize profitability. As semiconductor device critical dimensions become smaller and chips become more complex, and with customers inquiring about process capability metrics to make sure they get the highest quality product, there is a need for chip manufacturers to thoroughly analyze and define their process capabilities. The work in this thesis done in collaboration with Analog Devices Inc., a leading chip manufacturer, shows how the concept of design of experiments (DOE) and statistical regression modeling techniques can be implemented in a practical industrial setting to rigorously understand and mathematically characterize process variations in a semiconductor fabrication process (plasma ashing). New approaches are introduced to Analog Devices Inc. in calculating wafer statistics. Methodologies are developed that will help the company to choose the right experimental designs based on the objective (e.g. accurate prediction of the response variable, process optimization, process robustness, etc.) while taking into account the process, time, and cost constraints. Multiple regression modeling techniques are utilized to analyze the outcomes of the experiment and the results of these techniques are compared to each other in order to choose the right model needed to satisfy the objective. The statistical software JMP is used to tease out subtle implications of the outcomes of the DOE and formulate hypotheses about any anomalies. The DOEs are performed on two Gasonics Aura 3010 machines that carry out the plasma ashing process using the same process parameters in order to highlight not only the similarities but also the differences in the machines which come from factors like the intrinsic build and state of the machines. The findings and results identify opportunities for the development of new process improvement strategies, faster root cause analysis of failures, methods to systematically calibrate new equipment, update standard operating procedures, and opportunities for machine matching. The purpose of this thesis is to serve as a pedagogical document and template for the process engineers at Analog Devices Inc. in the future to perform DOEs on other processes and machines in the fabrication center.by Tanay Rahul Nerurkar.M. Eng. in Advanced Manufacturing and Desig
Interspecies Translation of Disease Networks Increases Robustness and Predictive Accuracy
Full text link© 2011 Anvar et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.Gene regulatory networks give important insights into the mechanisms underlying physiology and pathophysiology. The derivation of gene regulatory networks from high-throughput expression data via machine learning strategies is problematic as the reliability of these models is often compromised by limited and highly variable samples, heterogeneity in transcript isoforms, noise, and other artifacts. Here, we develop a novel algorithm, dubbed Dandelion, in which we construct and train intraspecies Bayesian networks that are translated and assessed on independent test sets from other species in a reiterative procedure. The interspecies disease networks are subjected to multi-layers of analysis and evaluation, leading to the identification of the most consistent relationships within the network structure. In this study, we demonstrate the performance of our algorithms on datasets from animal models of oculopharyngeal muscular dystrophy (OPMD) and patient materials. We show that the interspecies network of genes coding for the proteasome provide highly accurate predictions on gene expression levels and disease phenotype. Moreover, the cross-species translation increases the stability and robustness of these networks. Unlike existing modeling approaches, our algorithms do not require assumptions on notoriously difficult one-to-one mapping of protein orthologues or alternative transcripts and can deal with missing data. We show that the identified key components of the OPMD disease network can be confirmed in an unseen and independent disease model. This study presents a state-of-the-art strategy in constructing interspecies disease networks that provide crucial information on regulatory relationships among genes, leading to better understanding of the disease molecular mechanisms.This work was funded in part by the European Commission (PolyALA LSHM-CT-2005018675) and Muscular Dystrophy Association (68016) to SMvdM and MDA, European Community’s Seventh Framework Programme (FP7/2007–2013), ENGAGE project, grant agreement HEALTH-F4-2007-201413, and the Centre for Medical Systems Biology within the framework of the Netherlands Genomics Initiative (NGI)/Netherlands Organisation for Scientific Research (NWO)
Exploring the minimum bactericidal concentration and time kill kinetics of benzothiophene derivatives in gram-positive bacteria
No full textTo determine the minimum bactericidal concentration (MBC) and confirm minimum inhibitory concentration (MIC) of a benzothiophene derivative (#34) using the microdilution and
macrodilution assay against two gram-positive bacteria, including Staphylococcus aureus and Enterococcus faecalis.
● To explore the time and dose dependence bactericidal/bacteriostatic activity of the compound #34 using time kill assay
Uncertainty Propagation in Bilinear and Polynomial System for Probabilistic Threshold Detection
No full textUncertainty can be defined as imperfect or unknown information arising in a stochastic environment. Due to the very limited knowledge, it is difficult to propagate and quantify various uncertainties affecting the system to its next step. As a result, it has been a challenge to consider multiple uncertainties affecting the system in various fields, such as Fault Detection and Diagnosis. Fault detection has been an essential part of a large industrial and manufacturing system to take a proper corrective measure into account in a case of unexpected behavior. However, determining a robust threshold bound for fault detection is a big challenge. Several uncertainties affect the system (such as parametric uncertainties, experimental uncertainties, process noise, measurement noise, etc.). Ignoring the effects of various uncertainties (i.e., Deterministic Bound) can lead to a false alarm.Therefore, to design a robust threshold probabilistic-based technique is used where all unknown parameters are taken into account. However, the major problem lies in propagating these unknown parameters into the next time step with their limited knowledge. A novel Message Passage Bilinear Uncertainty Propagation (MPBUP) algorithm is being proposed, which is used to quantify and propagate various uncertainties affecting the dynamical system into the next time step. The main aim of the algorithm is to quantify and propagate various uncertain parameters affecting the system at each time step. Uncertainty is propagated in terms of mean and covariance at each algorithm iteration to find the overall effect. Therefore the primary research is to design and validate the proposed algorithm and to check the algorithm can be used to determine a probabilistic threshold. In the report, a detailed explanation of the algorithm for a trivial example is presented. The algorithm is then developed and implemented in MATLAB. Next, validation of the output generated through the algorithm is performed using Monte Carlo simulation. Finally, various analyses based on the MC simulation are discussed to support the results generated through the algorithm. An innovative approach is also discussed to extend the polynomial system algorithm as the proposed algorithm is limited to the bilinear system.Further, a detailed explanation is given on applying the algorithm on a general state-space model in terms of mathematics involved, which is further extended on applying the algorithm on a real-time application such as the Four Tank System. After successfully implementing the algorithm on the Four Tank System, the algorithm is used to propagate uncertainty into the dynamical system to determine the robust threshold. A robust threshold is found considering the effect of various uncertainty. The threshold found using the proposed algorithm is dynamic as it evolves based upon the state dynamics and satisfies the required condition. As a result presented algorithm satisfy all the requirement and can also be used in other applications. The algorithm was analyzed based upon various criteria to conclude this thesis, and a comparative study is conducted.Mechanical Engineering | Systems and Contro
Diversity of traditional medicinal plants in silvipastoral land use systems of Indian North Western Himalaya
No full text124-145The Indian Himalayan Region (IHR) is one of the world’s mega biodiversity hotspots with diverse landscapes. The IHR
harbour diverse agro-ecological conditions known for its silvipastoral land use systems for conservation and management of
biodiversity. The present study highlights the diversity of ethno-medicinal plants in silvipastoral land use systems of
Himachal Pradesh, North Western Himalaya along with their indigenous medicinal uses. The study was conducted using
semi-structured interviews with locals and Vaidya’s through participatory rural appraisal exercises, in 12 districts of study
region spanning across 4 agroclimatic zones. The study identified 201 species belonging to 73 families and 170 genera.
Fabaceae followed by Lamiaceae, Rosaceae, Poaceae were the dominant families. The study identified utilization of 197
angiosperm species, 3 gymnosperms and 2 pteridophyte species. The species diversity showed maximum distribution of
herbs (83), followed by trees (58) and shrubs (48). Leaves and root were the most frequently used part followed by fruits,
whole plant, tuber and seeds. Powder followed by paste, juice, decoction, and extracts were the frequently utilized
preparation methods for ethnomedicinal preparation for treatment of various ailments. Further the study attempts to address
threat categories and suggests conservation and management strategies for potential ethnomedicinal plants
Solvatochromism Of NNDAP-O-CH3
No full textThe solvatochromic properties of a novel fluorophore, 4-[2-[2-(dimethylamino)-3-pyridyl]ethynyl]anisole (NNDAP-O-CH3), developed by Dr. Tanay Kesharwani of The University of West Florida was studied. The absorption and emission spectra of the fluorophore in various solvents were measured. The ground state and singlet excited state dipole moments were determined using the Bilot-Kawski, Lippert-Mataga, Bakhshiev, and Reichardt correlation methods. The magnitude to which a certain solvent property contributes to the observed solvatochromic shifts was investigated using both Kamlet-Taft and Catalan models. The experimental system and environment are being computationally modeled in Gaussian16. Predictions of the software will be compared to experimental evidence to propose structural and dynamic factors contributing to the phenomenon as well as to predict other properties of the molecule
Hierarchical timing-driven partitioning and placement for symmetrical FPGAs
No full textField-programmable gate arrays (FPGAs) allow circuit designers to perform quick prototyping and development. In this thesis we attempt to partition and place a hierarchically described system on multiple FPGA chips so as to minimize the maximum delay through the system. We exploit the given hierarchy to achieve computational speedup. Delay estimation is done using an accurate empirical model. The major contributions of this thesis include multichip partitioning, accurate routing delay estimation and hierarchical timing-driven placement to avoid timing problems in FPGAs.First, we present a hierarchical partitioning algorithm that transforms the input hierarchical system into a structural hierarchy with minimum connectivity and equal FPGA chip area requirements among partitions at each hierarchical level. We address timing problems in the method by estimating path delays. Our delay model far outperforms conventional methods. The delay is assumed to be a function of path length, circuit size, fanout and congestion in the channels. An empirical model is developed by extensive simulations of various FPGA circuits. The structural hierarchy and delay estimation are then used to guide the hierarchical FPGA placement. This placement algorithm is a deterministic one. It consists of bottom-up clustering and a novel AND-OR tree-based hierarchical constraint satisfaction algorithm. It provides better results than flat-level iterative improvement algorithm based on simulated annealing with very high computational speedup. We show that it can place a large path-intensive circuit that cannot be placed at the flat level due to the combinatorial explosion.Finally, we integrate all algorithms to form a hierarchical timing-driven partitioning and placement system for symmetrical FPGAs. The structural hierarchy generated by hierarchical partitioning is refined by a child-stealing algorithm to reduce the ill effect of initial decisions on the partitions. The timing-driven placement algorithm is extended to multichip operation. The placement is passed through a compaction step to reduce the unoccupied areas on the chips. As a final stage, we developed a flat-level iterative improvement algorithm to perform concurrent timing-driven partitioning and placement. This tool is an optional operation in our system to refine the solution. Being an iterative tool, it incurs a high computational overhead. Hence, it is judicially used when the maximum delay through the circuit is not acceptable. Our system is applicable to large industrial benchmark circuits. The results show that our system provides better results than iterative improvement based on constrained simulated annealing with a very high computational speedup.Made available in DSpace on 2011-05-07T11:53:10Z (GMT). No. of bitstreams: 2
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Ethics in AI
No full textPart 3: AI Philosophy, Ethics and GovernanceInternational audienceThe launch of various AI systems has been one of the main highlights of the industry. Alongside the enormous and revolutionary benefits, AI can cause numerous problems (usually resulting from poor design) and people have recently started to get serious about researching ways to make AI safer. Many of the AI safety concerns sound like science fiction, problems that might occur with very strong AI systems that are still years away, making these issues difficult to investigate. We don’t know what such potential AI systems would be like, but similar issues exist with AI systems that are currently in progress or even running in the real world. The author addresses the possible implications in this article, outlining some important approaches in terms of software development methodologies and philosophy that we can start working on right now to support us with current AI systems and, hopefully, future system
Comparative efficacy of microwave, visible light and ultrasound irradiation for green synthesis of dihydropyrimidinones in fruit juice medium
No full textCounterface Soil Type and Loading Condition Effects on Granular/Cohesive Soil – Geofoam Interface Shear Behavior
No full textSoil – geofoam interfaces have been studied through an extensive experimental program by performing multiple series of interface shear tests using two different granular soils (i.e. beach sand and construction material sand) and one cohesive soil (i.e. bentonite clay) as well as a soil mixture containing 75% sand and 25% clay by dry weight at distinct loading conditions (i.e. normal stresses (?): 25, 100, 250; low, moderate, high loading conditions, respectively). Using the shear stress versus horizontal displacement curves obtained, some important engineering design parameters including peak shear stress, residual shear stress, interface sensitivity (i.e., peak/residual ratio) and displacement required to reach peak stress have been determined and the variations in those interface mechanical properties as a function of loading condition and counterface soil type have been investigated. It was shown that the peak as well as residual shear stresses increased with an increase in normal stress for all the interface systems tested. Further, the granular soil (sand) interfaces demonstrated relatively larger frictional strengths (both peak and residual) as compared to both the cohesive soil (clay) interface and the sand/clay admixture soil interface. Additionally, the higher the angularity of granular soil particles became, the larger the interface shear strengths (peak and residual), when sheared against geofoams, developed in light of experimental results attained as a result of interface shear tests on different material combinations. For comparison, the detected peak strength at average for the construction material sand, the beach sand, and the sand/clay admixture soil interfaces as compared to the bentonite clay interface were improved 59.8%, 43.4%, and 20.3%, respectively. Additionally, the detected residual strength at average for the construction material sand, the beach sand, and the sand/clay admixture soil interfaces as compared to the bentonite clay interface were improved 53.9%, 28.6%, and 15.4%, respectively. © Author(s) 2024
