Semi-Supervised Classification Using Sparse Gaussian Process Regression

Gaussian Processes (GPs) are promising Bayesian methods for classification and regression problems. They have also been used for semi-supervised learning tasks. In this paper, we propose a new algorithm for solving semi-supervised binary classification problem using sparse GP regression (GPR) models. It is closely related to semi-supervised learning based on support vector regression (SVR) and maximum margin clustering. The proposed algorithm is simple and easy to implement. It gives a sparse solution directly unlike the SVR based algorithm. Also, the hyperparameters are estimated easily without resorting to expensive cross-validation technique. Use of sparse GPR model helps in making the proposed algorithm scalable. Preliminary results on synthetic and real-world data sets demonstrate the efficacy of the new algorithm.

Validation of Decision Tables Used in Process Control

Process control rules may be specified using decision tables. Such a specification is superior when logical decisions to be taken in control dominate. In this paper we give a method of detecting redundancies, incompleteness, and contradictions in such specifications. Using such a technique thus ensures the validity of the specifications.

Dynamic multi-relational Chinese restaurant process for analyzing influences on users in social media

We study the problem of analyzing influence of various factors affecting individual messages posted in social media. The problem is challenging because of various types of influences propagating through the social media network that act simultaneously on any user. Additionally, the topic composition of the influencing factors and the susceptibility of users to these influences evolve over time. This problem has not been studied before, and off-the-shelf models are unsuitable for this purpose. To capture the complex interplay of these various factors, we propose a new non-parametric model called the Dynamic Multi-Relational Chinese Restaurant Process. This accounts for the user network for data generation and also allows the parameters to evolve over time. Designing inference algorithms for this model suited for large scale social-media data is another challenge. To this end, we propose a scalable and multi-threaded inference algorithm based on online Gibbs Sampling. Extensive evaluations on large-scale Twitter and Face book data show that the extracted topics when applied to authorship and commenting prediction outperform state-of-the-art baselines. More importantly, our model produces valuable insights on topic trends and user personality trends beyond the capability of existing approaches.

Towards robust part tracking in an automated manufacturing process using RFID

Automated Identification and in particular, Radio Frequency Identification (RFID) promises to assist with the automation of mass customised production processes. RFID has long been used to gather a history or trace of part movements, but the use of it as an integral part of the control process is yet to be fully exploited. Such use places stringent demands on the quality of the sensor data and the method used to interpret that data. in particular, this paper focuses on the issue of correctly identifying, tracking and dealing with aggregated objects with the use of RFID. The presented approach is evaluated in the context of a laboratory manufacturing system that produces customised gift boxes. Copyright © 2005 IFAC.

A framework for distributed intelligent automation systems developments

This paper proposes a pragmatic framework that has been developed for classifying and analyzing developments in distributed automation and information systems - especially those that have been labeled intelligent systems for different reasons. The framework dissects the different stages in the standard feedback process and assesses distribution in terms of the level of granularity of the organization that is being considered. The framework has been found to be useful in comparing and assessing different distributed industrial control paradigms and also for examining common features of different development projects - especially those that might be sourced from different sectors or domains. © 2012 IFAC.

A framework for distributed intelligent automation systems developments

This chapter proposes a simple and pragmatic framework that has been developed for classifying and analyzing developments in distributed automation and information systems - especially those that have been labelled intelligent systems for different reasons. The framework dissects the different stages in the standard feedback process and assesses distribution in terms of the level of granularity of the organization that is being considered. The framework has been found to be useful in comparing and assessing different distributed industrial control paradigms and also for examining common features of different development projects - especially those that might be sourced from different sectors or domains. © Springer-Verlag Berlin Heidelberg 2013.

Introducing Automated Management Through Iteratively Increased Automation and Indicators

Introducing automation into a managed environment includes significant initial overhead and abstraction, creating a disconnect between the administrator and the system. In order to facilitate the transition to automated management, this paper proposes an approach whereby automation increases gradually, gathering data from the task deployment process. This stored data is analysed to determine the task outcome status and can then be used for comparison against future deployments of the same task and alerting the administrator to deviations from the expected outcome. Using a machinelearning
approach, the automation tool can learn from the administrator's reaction to task failures and eventually react to faults autonomously.

Modelling lay-up automation and production rate interaction on the cost of large stiffened panel components

This paper presents an integrated design and costing method for large stiffened panels for the purpose of investigating the influence and interaction of lay-up technology and production rate on manufacturing cost. A series of wing cover panels (≈586kg, 19·9m2) have been sized with realistic requirements considering manual and automated lay-up routes. The integrated method has enabled the quantification of component unit cost sensitivity to changes in annual production rate and employed equipment maximum deposition rate. Moreover the results demonstrate the interconnected relationship between lay-up process and panel design, and unit cost. The optimum unit cost solution when using automated lay-up is a combination of the minimum deposition rate and minimum number of lay-up machines to meet the required production rate. However, the location of the optimum unit cost, at the boundaries between the number of lay-up machines required, can make unit cost very sensitive to small changes in component design, production rate, and equipment maximum deposition rate. - See more at: http://aerosociety.com/News/Publications/Aero-Journal/Online/1941/Modelling-layup-automation-and-production-rate-interaction-on-the-cost-of-large-stiffened-panel-components#sthash.0fLuu9iG.dpuf

Process variation tolerant low power DCT architecture

2-D Discrete Cosine Transform (DCT) is widely used as the core of digital image and video compression. In this paper, we present a novel DCT architecture that allows aggressive voltage scaling by exploiting the fact that not all intermediate computations are equally important in a DCT system to obtain "good" image quality with Peak Signal to Noise Ratio(PSNR) > 30 dB. This observation has led us to propose a DCT architecture where the signal paths that are less contributive to PSNR improvement are designed to be longer than the paths that are more contributive to PSNR improvement. It should also be noted that robustness with respect to parameter variations and low power operation typically impose contradictory requirements in terms of architecture design. However, the proposed architecture lends itself to aggressive voltage scaling for low-power dissipation even under process parameter variations. Under a scaled supply voltage and/or variations in process parameters, any possible delay errors would only appear from the long paths that are less contributive towards PSNR improvement, providing large improvement in power dissipation with small PSNR degradation. Results show that even under large process variation and supply voltage scaling (0.8V), there is a gradual degradation of image quality with considerable power savings (62.8%) for the proposed architecture when compared to existing implementations in 70 nm process technology.

A dynamic sampling methodology for plasma etch processes using Gaussian process regression

Plasma etch is a key process in modern semiconductor manufacturing facilities as it offers process simplification and yet greater dimensional tolerances compared to wet chemical etch technology. The main challenge of operating plasma etchers is to maintain a consistent etch rate spatially and temporally for a given wafer and for successive wafers processed in the same etch tool. Etch rate measurements require expensive metrology steps and therefore in general only limited sampling is performed. Furthermore, the results of measurements are not accessible in real-time, limiting the options for run-to-run control. This paper investigates a Virtual Metrology (VM) enabled Dynamic Sampling (DS) methodology as an alternative paradigm for balancing the need to reduce costly metrology with the need to measure more frequently and in a timely fashion to enable wafer-to-wafer control. Using a Gaussian Process Regression (GPR) VM model for etch rate estimation of a plasma etch process, the proposed dynamic sampling methodology is demonstrated and evaluated for a number of different predictive dynamic sampling rules. © 2013 IEEE.

Examination timetabling automation using hybrid meta-heuristics

Trabalho de projeto realizado para obtenção do grau de Mestre em Engenharia Informática e de Computadores

Automation of Chemical Spray Pyrolysis Unit and Fabrication of Sprayed CuInS2/In2S3 Solar Cell

Aim of the present work was to automate CSP process, to deposit and characterize CuInS2/In2S3 layers using this system and to fabricate devices using these films.An automated spray system for the deposition of compound semiconductor thin films was designed and developed so as to eliminate the manual labour involved in spraying and facilitate standardization of the method. The system was designed such that parameters like spray rate, movement of spray head, duration of spray, temperature of substrate, pressure of carrier gas and height of the spray head from the substrate could be varied. Using this system, binary, ternary as well as quaternary films could be successfully deposited.The second part of the work deal with deposition and characterization of CuInS2 and In2S3 layers respectively.In the case of CuInS2 absorbers, the effects of different preparation conditions and post deposition treatments on the optoelectronic, morphological and structural properties were investigated. It was observed that preparation conditions and post deposition treatments played crucial role in controlling the properties of the films. The studies in this direction were useful in understanding how the variation in spray parameters tailored the properties of the absorber layer. These results were subsequently made use of in device fabrication process.Effects of copper incorporation in In2S3 films were investigated to find how the diffusion of Cu from CuInS2 to In2S3 will affect the properties at the junction. It was noticed that there was a regular variation in the opto-electronic properties with increase in copper concentration.Devices were fabricated on ITO coated glass using CuInS2 as absorber and In2S3 as buffer layer with silver as the top electrode. Stable devices could be deposited over an area of 0.25 cm2, even though the efficiency obtained was not high. Using manual spray system, we could achieve devices of area 0.01 cm2 only. Thus automation helped in obtaining repeatable results over larger areas than those obtained while using the manual unit. Silver diffusion on the cells before coating the electrodes resulted in better collection of carriers.From this work it was seen CuInS2/In2S3 junction deposited through automated spray process has potential to achieve high efficiencies.