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15 research outputs found

Development of constrained fuzzy logic for modeling biological regulatory networks and predicting contextual therapeutic effects

Author: Morris Melody K
Publication venue: Massachusetts Institute of Technology
Publication date: 01/01/2012
Field of study

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Biological Engineering, 2012.Cataloged from PDF version of thesis.Includes bibliographical references (p. 199-213).Upon exposure to environmental cues, protein modifications form a complex signaling network that dictates cellular response. In this thesis, we develop methods for using continuous logic-based models to aide our understanding of these signaling networks and facilitate data interpretation. We present a novel modeling framework called constrained fuzzy logic (cFL) that maintains a simple logic-based description of interactions with AND, OR, and NOT gates, but allows for intermediate species activities with mathematical functions relating input and output values (transfer functions). We first train a prior knowledge network (PKN) to data with cFL, which reveals what aspects of the dataset agree or disagree with prior knowledge. The cFL models are trained to a dataset describing signaling proteins in a hepatocellular carcinoma cell line after exposure to ligand cues in the presence or absence of small molecule inhibitors. We find that multiple models with differing topology and parameters explain the data equally well, and it is crucial to consider this non-identifiability during model training and subsequence analysis. Our trained models generate new biological understanding of network crosstalk as well as quantitative predictions of signaling protein activation. In our next applications of cFL, we explore the ability of models either constructed based solely on prior knowledge or trained to dedicated biochemical data to make predictions that answer the following questions: 1) What perturbations to species in the system are effective at accomplishing a clinical goal? and 2) In what environmental conditions are these perturbations effective? We find that we are able to make accurate predictions in both cases. Thus, we offer cFL as a flexible modeling methodology to assist data interpretation and hypothesis generation for choice of therapeutic targets.by Melody K. Morris.Ph.D

DSpace@MIT

Towards Automated Network Configuration Management

Author: Elmansor Khalid
Publication venue: DePaul University
Publication date: 01/01/2013
Field of study

Modern networks are designed to satisfy a wide variety of competing goals related to network operation requirements such as reachability, security, performance, reliability and availability. These high level goals are realized through a complex chain of low level configuration commands performed on network devices. As networks become larger, more complex and more heterogeneous, human errors become the most significant threat to network operation and the main cause of network outage. In addition, the gap between high-level requirements and low-level configuration data is continuously increasing and difficult to close. Although many solutions have been introduced to reduce the complexity of configuration management, network changes, in most cases, are still manually performed via low--level command line interfaces (CLIs). The Internet Engineering Task Force (IETF) has introduced NETwork CONFiguration (NETCONF) protocol along with its associated data--modeling language, YANG, that significantly reduce network configuration complexity. However, NETCONF is limited to the interaction between managers and agents, and it has weak support for compliance to high-level management functionalities. We design and develop a network configuration management system called AutoConf that addresses the aforementioned problems. AutoConf is a distributed system that manages, validates, and automates the configuration of IP networks. We propose a new framework to augment NETCONF/YANG framework. This framework includes a Configuration Semantic Model (CSM), which provides a formal representation of domain knowledge needed to deploy a successful management system. Along with CSM, we develop a domain--specific language called Structured Configuration language to specify configuration tasks as well as high--level requirements. CSM/SCL together with NETCONF/YANG makes a powerful management system that supports network--wide configuration. AutoConf supports two levels of verifications: consistency verification and behavioral verification. We apply a set of logical formalizations to verifying the consistency and dependency of configuration parameters. In behavioral verification, we present a set of formal models and algorithms based on Binary Decision Diagram (BDD) to capture the behaviors of forwarding control lists that are deployed in firewalls, routers, and NAT devices. We also adopt an enhanced version of Dyna-Q algorithm to support dynamic adaptation of network configuration in response to changes occurred during network operation. This adaptation approach maintains a coherent relationship between high level requirements and low level device configuration. We evaluate AutoConf by running several configuration scenarios such as interface configuration, RIP configuration, OSPF configuration and MPLS configuration. We also evaluate AutoConf by running several simulation models to demonstrate the effectiveness and the scalability of handling large-scale networks

CiteSeerX

Via Sapientiae: The Institutional Repository at DePaul University

Design-for-Test and Test Optimization Techniques for TSV-based 3D Stacked ICs

Author: Noia Brandon Robert
Publication venue
Publication date: 01/01/2014
Field of study

As integrated circuits (ICs) continue to scale to smaller dimensions, long interconnectshave become the dominant contributor to circuit delay and a significant component ofpower consumption. In order to reduce the length of these interconnects, 3D integrationand 3D stacked ICs (3D SICs) are active areas of research in both academia and industry.3D SICs not only have the potential to reduce average interconnect length and alleviatemany of the problems caused by long global interconnects, but they can offer greater designflexibility over 2D ICs, significant reductions in power consumption and footprint inan era of mobile applications, increased on-chip data bandwidth through delay reduction,and improved heterogeneous integration.Compared to 2D ICs, the manufacture and test of 3D ICs is significantly more complex.Through-silicon vias (TSVs), which constitute the dense vertical interconnects in adie stack, are a source of additional and unique defects not seen before in ICs. At the sametime, testing these TSVs, especially before die stacking, is recognized as a major challenge.The testing of a 3D stack is constrained by limited test access, test pin availability,power, and thermal constraints. Therefore, efficient and optimized test architectures areneeded to ensure that pre-bond, partial, and complete stack testing are not prohibitivelyexpensive.Methods of testing TSVs prior to bonding continue to be a difficult problem due to testaccess and testability issues. Although some built-in self-test (BIST) techniques have beenproposed, these techniques have numerous drawbacks that render them impractical. In this dissertation, a low-cost test architecture is introduced to enable pre-bond TSV test throughTSV probing. This has the benefit of not needing large analog test components on the die,which is a significant drawback of many BIST architectures. Coupled with an optimizationmethod described in this dissertation to create parallel test groups for TSVs, test time forpre-bond TSV tests can be significantly reduced. The pre-bond probing methodology isexpanded upon to allow for pre-bond scan test as well, to enable both pre-bond TSV andstructural test to bring pre-bond known-good-die (KGD) test under a single test paradigm.The addition of boundary registers on functional TSV paths required for pre-bondprobing results in an increase in delay on inter-die functional paths. This cost of testarchitecture insertion can be a significant drawback, especially considering that one benefitof 3D integration is that critical paths can be partitioned between dies to reduce their delay.This dissertation derives a retiming flow that is used to recover the additional delay addedto TSV paths by test cell insertion.Reducing the cost of test for 3D-SICs is crucial considering that more tests are necessaryduring 3D-SIC manufacturing. To reduce test cost, the test architecture and testscheduling for the stack must be optimized to reduce test time across all necessary testinsertions. This dissertation examines three paradigms for 3D integration - hard dies, firmdies, and soft dies, that give varying degrees of control over 2D test architectures on eachdie while optimizing the 3D test architecture. Integer linear programming models are developedto provide an optimal 3D test architecture and test schedule for the dies in the 3Dstack considering any or all post-bond test insertions. Results show that the ILP modelsoutperform other optimization methods across a range of 3D benchmark circuits.In summary, this dissertation targets testing and design-for-test (DFT) of 3D SICs.The proposed techniques enable pre-bond TSV and structural test while maintaining arelatively low test cost. Future work will continue to enable testing of 3D SICs to moveindustry closer to realizing the true potential of 3D integration.Dissertatio

DukeSpace

Design of an intelligent embedded system for condition monitoring of an industrial robot

Author: Jaber Alaa Abdulhady
Publication venue: Newcastle University
Publication date: 01/01/2016
Field of study

PhD ThesisIndustrial robots have long been used in production systems in order to improve productivity, quality and safety in automated manufacturing processes. There are significant implications for operator safety in the event of a robot malfunction or failure, and an unforeseen robot stoppage, due to different reasons, has the potential to cause an interruption in the entire production line, resulting in economic and production losses. Condition monitoring (CM) is a type of maintenance inspection technique by which an operational asset is monitored and the data obtained is analysed to detect signs of degradation, diagnose the causes of faults and thus reduce maintenance costs. So, the main focus of this research is to design and develop an online, intelligent CM system based on wireless embedded technology to detect and diagnose the most common faults in the transmission systems (gears and bearings) of the industrial robot joints using vibration signal analysis. To this end an old, but operational, PUMA 560 robot was utilized to synthesize a number of different transmission faults in one of the joints (3 - elbow), such as backlash between the gear pair, gear tooth and bearing faults. A two-stage condition monitoring algorithm is proposed for robot health assessment, incorporating fault detection and fault diagnosis. Signal processing techniques play a significant role in building any condition monitoring system, in order to determine fault-symptom relationships, and detect abnormalities in robot health. Fault detection stage is based on time-domain signal analysis and a statistical control chart (SCC) technique. For accurate fault diagnosis in the second stage, a novel implementation of a time-frequency signal analysis technique based on the discrete wavelet transform (DWT) is adopted. In this technique, vibration signals are decomposed into eight levels of wavelet coefficients and statistical features, such as standard deviation, kurtosis and skewness, are obtained at each level and analysed to extract the most salient feature related to faults; the artificial neural network (ANN) is then used for fault classification. A data acquisition system based on National Instruments (NI) software and hardware was initially developed for preliminary robot vibration analysis and feature extraction. The transmission faults induced in the robot can change the captured vibration spectra, and the robot’s natural frequencies were established using experimental modal analysis, and also the fundamental fault frequencies for the gear transmission and bearings were obtained and utilized for preliminary robot condition monitoring. In addition to simulation of different levels of backlash fault, gear tooth and bearing faults which have not been previously investigated in industrial robots, with several levels of ii severity, were successfully simulated and detected in the robot’s joint transmission. The vibration features extracted, which are related to the robot healthy state and different fault types, using the data acquisition system were subsequently used in building the SCC and ANN, which were trained using part of the measured data set that represents the robot operating range. Another set of data, not used within the training stage, was then utilized for validation. The results indicate the successful detection and diagnosis of faults using the key extracted parameters. A wireless embedded system based on the ZigBee communication protocol was designed for the application of the proposed CM algorithm in real-time, using an Arduino DUE as the core of the wireless sensor unit attached on the robot arm. A Texas Instruments digital signal processor (TMS320C6713 DSK board) was used as the base station of the wireless system on which the robot’s fault diagnosis algorithm is run. To implement the two stages of the proposed CM algorithm on the designed embedded system, software based on the C programming language has been developed. To demonstrate the reliability of the designed wireless CM system, experimental validations were performed, and high reliability was shown in the detection and diagnosis of several seeded faults in the robot. Optimistically, the established wireless embedded system could be envisaged for fault detection and diagnostics on any type of rotating machine, with the monitoring system realized using vibration signal analysis. Furthermore, with some modifications to the system’s hardware and software, different CM techniques such as acoustic emission (AE) analysis or motor current signature analysis (MCSA), can be applied.Iraqi government, represented by the Ministry of Higher Education and Scientific Research, the Iraqi Cultural Attaché in London, and the University of Technology in Baghda

Newcastle University eTheses