Recurrent neural network approach for cyclic job shop scheduling problem

While cyclic scheduling is involved in numerous real-world applications, solving the derived problem is still of exponential complexity. This paper focuses specifically on modelling the manufacturing application as a cyclic job shop problem and we have developed an efficient neural network approach to minimise the cycle time of a schedule. Our approach introduces an interesting model for a manufacturing production, and it is also very efficient, adaptive and flexible enough to work with other techniques. Experimental results validated the approach and confirmed our hypotheses about the system model and the efficiency of neural networks for such a class of problems.     

Limit cycles induced in type-1 linear systems with PID-type of relay feedback

This article investigates the limit cycles within type-1 linear systems under PID-type of relay feedback. The problem is generalised from the identification of friction models of servo mechanical systems via limit-cycle experiments under dual-channel relay feedback. Locations of limit cycles are given so that the exact durations between two consecutive switchings of relays can be determined via numerical computation. After this, local stability of limit cycles can be checked via the Jacobian of Poincaré map. Examples are analysed using proposed theorems.     

Potential of spectroscopic data sets for sugarcane thrips (Fulmekiola serrata Kobus) damage detection

Sugarcane thrips was detected in South African sugarcane in 2004. Since then it has become widespread in South Africa. The South African Sugarcane Research Institute (SASRI) conducts field surveys to monitor this pest, but this is time intensive and costly. As a first step towards evaluation of remote sensing for thrips monitoring, a preliminary experiment and analysis at leaf level were conducted using a handheld field spectroradiometer covering the 350 to 2500 nm range of the electromagnetic spectrum to detect sugarcane thrips damage. Reflectance spectra of sugarcane leaves with different levels of thrips damage, from two popular varieties (N19 and N12), were measured and statistically analysed using one-way analysis of variance, sensitivity analysis and canonical discriminant analysis. The results of the analyses showed that there were significant differences in spectral reflectance and derived variables used in the study at the different levels of damage. The red edge region of the visible portion gave the highest significant differences and levels of separability among the damage classes. It is hypothesized that this might be associated with chlorophyll and nitrogen deficiencies induced by thrips.     

Minimizing control variation in nonlinear optimal control

In any real system, changing the control signal from one value to another will usually cause wear and tear on the system’s actuators. Thus, when designing a control law, it is important to consider not just predicted system performance, but also the cost associated with changing the control action. This latter cost is almost always ignored in the optimal control literature. In this paper, we consider a class of optimal control problems in which the variation of the control signal is explicitly penalized in the cost function. We develop an effective computational method, based on the control parameterization approach and a novel transformation procedure, for solving this class of optimal control problems. We then apply our method to three example problems in fisheries, train control, and chemical engineering.     

BSEM estimation of network effect and customer orientation empowerment on trust in social media and network environment

This paper presents a stochastic model that identifies network effect and customer orientation empowerment as strong antecedents of trustworthiness and trust in social media network environment. As Trust is emerging as a critical influencer of consumer behavior in organizations, social media has become the facilitator or the enabler of this influence. This paper aims to explore and examine the relationships amongst the antecedents of trust in the context of the social media network environment via Bayesian estimation and testing of the structural equation model. In facilitating the estimation of the stochastic model, a survey was conducted on 255 social media users. A series of statistical analyses were conducted prior to the estimation using Bayesian Markov Chain Monte Carlo (MCMC). Results showed that network effect and customer orientation empowerment were significant predictors of trustworthiness and trust. Bayesian MCMC results confirmed that the findings were consistent with the literature.     

Soot Particle Aerosol Mass Spectrometer: Development,Validation, and Initial Application

The Soot Particle Aerosol Mass Spectrometer (SP-AMS) was developed to measure the chemical and physical properties of particles containing refractory black carbon (rBC). The SP-AMS is an Aerodyne Aerosol Mass Spectrometer (AMS) equipped with an intracavity laser vaporizer (1064 nm) based on the Single Particle Soot Photometer (SP2) design, in addition to the resistively heated, tungsten vaporizer used in a standard AMS. The SP-AMS can be operated with the laser vaporizer alone, with both the laser and tungsten vaporizers, or with the tungsten vaporizer alone. When operating with only the laser vaporizer, the SP-AMS is selectively sensitive to laser-light absorbing particles, such as ambient rBC-containing particles as well as metal nanoparticles, and measures both the refractory and nonrefractory components. When operated with both vaporizers and modulating the laser on and off, the instrument measures the refractory components of absorbing particles and the nonrefractory particulate matter of all sampled particles. The SP-AMS design, mass spectral interpretation, calibration, and sensitivity are described. Instrument calibrations yield a sensitivity of greater than 140 carbon ions detected per picogram of rBC mass sampled, a 3σ detection limit of less than 0.1 μg·m^?3 for 60 s averaging, and a mass-specific ionization efficiency relative to particulate nitrate of 0.2 ± 0.1. Sensitivities were found to vary depending upon laser-particle beam overlap. The utility of the instrument to characterize ambient rBC aerosol is demonstrated.

Copyright 2012 American Association for Aerosol Research     

Free-standing thick-film piezoelectric device

A free-standing thick-film cantilever sensor structure is presented. Such devices find use in applications such as vibration detection or energy harvesting. The structure was fabricated by screen printing layers of lead zirconate titanate between silver/palladium electrodes and co-firing the layers together with a carbon sacrificial layer (deposited underneath) in an air environment at a temperature of 850degC. The free-standing structure, of dimensions 18 mm long by 9 mm wide and thickness of 50 mum, was found to produce electrical powers of up to 95 nW at an acceleration level of 9.81 m/s² (1 g), when driving a 60 kcopy load resistance.     

Empirical Correlations for Estimating Filtrate Volume of Water Based Drilling Fluids

Standard American Petroleum Institute (API) filter press is generally used for identifying the filtrate volume of drilling fluids and works only at very low pressures. In fact, during a drilling operation, at downhole conditions, the pressures encountered are significantly higher than what is used during standard API filter press tests. A relationship between the well-known fluid properties and the filtrate volume test is developed. In this study, experiments have been conducted for different water-clay mixtures with varying concentrations at different pressure values by using standard API filter press and HP&HT (high-pressure high-temperature) filter press. The relationship between physical and chemical properties of water-clay mixtures and filtrate volume is analyzed. An empirical correlation has been developed for estimating filtrate volume using basic information of the mud (i.e., rotational viscometer readings, density, pressure, cation exchange capacity, and chemical composition). The developed correlation can estimate filtrate volume with an error less than 20% for a wide range of pressure values.