Mathematical model and rule extraction for tool wear monitoring problem using nature inspired techniques

In this paper, pattern classification problem in tool wear monitoring is solved using nature inspired techniques such as Genetic Programming(GP) and Ant-Miner (AM). The main advantage of GP and AM is their ability to learn the underlying data relationships and express them in the form of mathematical equation or simple rules. The extraction of knowledge from the training data set using GP and AM are in the form of Genetic Programming Classifier Expression (GPCE) and rules respectively. The GPCE and AM extracted rules are then applied to set of data in the testing/validation set to obtain the classification accuracy. A major attraction in GP evolved GPCE and AM based classification is the possibility of obtaining an expert system like rules that can be directly applied subsequently by the user in his/her application. The performance of the data classification using GP and AM is as good as the classification accuracy obtained in the earlier study.

A fluctuation-based characterization of athermal phase transitions:Application to shape memory alloys

We employ a fluctuation-based technique to investigate the athermal component associated with martensite phase transition, which is a prototype of temperature-driven structural transformation. Statistically, when the phase transition is purely athermal, we find that the temporal sequence of avalanches under constant drive is insensitive to the drive rate. We have used fluctuations in electrical resistivity or noise in nickel titanium shape memory alloys in three different forms: a thin film exhibiting well-defined transition temperatures,a highly disordered film, and a bulk wire of rectangular cross-section. Noise is studied in the realm of dynamic transition,viz.while the temperature is being ramped, which probes into the kinetics of the transformation at real time scales,and could probably stand out as a promising tool for material testing in various other systems, including nanoscale devices.

Search for chaos in neutron star systems: Is Cyg X-3 a black hole?

The accretion disk around a compact object is a nonlinear general relativistic system involving magnetohydrodynamics. Naturally, the question arises whether such a system is chaotic (deterministic) or stochastic (random) which might be related to the associated transport properties whose origin is still not confirmed. Earlier, the black hole system GRS 1915+105 was shown to be low-dimensional chaos in certain temporal classes. However, so far such nonlinear phenomena have not been studied fairly well for neutron stars which are unique for their magnetosphere and kHz quasi-periodic oscillation (QPO). On the other hand, it was argued that the QPO is a result of nonlinear magnetohydrodynamic effects in accretion disks. If a neutron star exhibits chaotic signature, then what is the chaotic/correlation dimension? We analyze RXTE/PCA data of neutron stars Sco X-1 and Cyg X-2, along with the black hole Cyg X-1 and the unknown source Cyg X-3, and show that while Sco X-1 and Cyg X-2 are low dimensional chaotic systems, Cyg X-1 and Cyg X-3 are stochastic sources. Based on our analysis, we argue that Cyg X-3 may be a black hole.

Fuzzy waste load allocation model: a multiobjective approach

Fuzzy Waste Load Allocation Model (FWLAM), developed in an earlier study, derives the optimal fractional levels, for the base flow conditions, considering the goals of the Pollution Control Agency (PCA) and dischargers. The Modified Fuzzy Waste Load Allocation Model (MFWLAM) developed subsequently is a stochastic model and considers the moments (mean, variance and skewness) of water quality indicators, incorporating uncertainty due to randomness of input variables along with uncertainty due to imprecision. The risk of low water quality is reduced significantly by using this modified model, but inclusion of new constraints leads to a low value of acceptability level, A, interpreted as the maximized minimum satisfaction in the system. To improve this value, a new model, which is a combination Of FWLAM and MFWLAM, is presented, allowing for some violations in the constraints of MFWLAM. This combined model is a multiobjective optimization model having the objectives, maximization of acceptability level and minimization of violation of constraints. Fuzzy multiobjective programming, goal programming and fuzzy goal programming are used to find the solutions. For the optimization model, Probabilistic Global Search Lausanne (PGSL) is used as a nonlinear optimization tool. The methodology is applied to a case study of the Tunga-Bhadra river system in south India. The model results in a compromised solution of a higher value of acceptability level as compared to MFWLAM, with a satisfactory value of risk. Thus the goal of risk minimization is achieved with a comparatively better value of acceptability level.

Fluorescence polarization as a tool to study lectin-sugar interaction. An investigation of the binding of 4-methylumbelliferyl beta-D-galactopyranoside to Abrus precatorious agglutinin

Polarization of ligand fluorescence was used to study the binding of 4-methylumbelliferyl beta-D-galactopyranoside (MeUmb-Galp) to Abrus precatorious agglutinin. The binding of the fluorescent sugar to the lectin led to considerable polarization of the MeUmb-Galp fluorescence, which was also quenched by about 30% on binding to the lectin. The binding of the fluorescent sugar was carbohydrate-specific, as evidenced by inhibition of both fluorescence polarization and quenching when lectin was preincubated with lactose. The association constant as determined by fluorescence polarization is 1.42 x 10(4) M-1 at 25 degrees C and is in excellent agreement with those determined by fluorescence quenching (Ka = 1.51 x 10(4) M-1) and equilibrium dialysis (Ka = 1.62 x 10(4) M-1) at 25 degrees C. The numbers of binding sites as determined by fluorescence polarization, quenching and equilibrium dialysis agree very well with one another, n being equal to 2.0 +/- 0.05. The consistency between the association constant value determined by fluorescence polarization, quenching and equilibrium dialysis shows the validity of this approach to study lectin-sugar interaction.

Metamodeling approach to predict friction factor of alluvial channel

The flow resistance of an alluvial channel flow is not only affected by the Reynolds number and the roughness conditions but also the Froude number. Froude number is the most basic parameter in the case of the alluvial channel, thus effect of Froude number on resistance to flow should be considered in the formulation of the friction factor, which is not in the case of present available resistance equations. At present, no generally acceptable quantitative description of the effects of the Froude number on hydraulic resistance has been developed. Metamodeling technique, which is particularly useful in modeling a complex processes or where knowledge of the physics is limited, is presented as a tool complimentary to modeling friction factor in alluvial channels. Present work uses, a radial basis metamodel, which is a type of neural network modeling, to find the effect of Froude number on the flow resistance. Based on the experimental data taken from different sources, it has been found that the predicting capability of the present model is on acceptable level. Present work also tries in formulating an empirical equation for resistance in alluvial channel comprising all the three majorm, parameters, namely, roughness parameter, Froude number and Reynolds number. (C) 2009 Elsevier B.V. All rights reserved.

A combinatorial procurement auction for QoS-aware web services

Business processes and application functionality are becoming available as internal web services inside enterprise boundaries as well as becoming available as commercial web services from enterprise solution vendors and web services marketplaces. Typically there are multiple web service providers offering services capable of fulfilling a particular functionality, although with different Quality of Service (QoS). Dynamic creation of business processes requires composing an appropriate set of web services that best suit the current need. This paper presents a novel combinatorial auction approach to QoS aware dynamic web services composition. Such an approach would enable not only stand-alone web services but also composite web services to be a part of a business process. The combinatorial auction leads to an integer programming formulation for the web services composition problem. An important feature of the model is the incorporation of service level agreements. We describe a software tool QWESC for QoS-aware web services composition based on the proposed approach.

Seismic Microzonation: A Tool for Disaster Mitigation Planning

Seismic microzonation has generally been recognized as the most accepted tool in seismic hazard assessment and risk evaluation. In general, risk reduction can be done by reducing the hazard, the vulnerability or the value at risk. Since the earthquake hazard can not be reduced, one has to concentrate on vulnerability and value at risk. The vulnerability of an urban area / municipalities depends on the vulnerability of infrastructure and redundancies within the infrastructure. The earthquake risk is the damage to buildings along with number of people that are killed / hurt and the economic losses during the event due to an earthquake with a return period corresponding to this time period. The principal approaches one can follow to reduce these losses are to avoid, if possible, high hazard areas for the siting of buildings and infrastructure, and further ensure that the buildings and infrastructure are designed and constructed to resist expected earthquake loads. This can be done if one can assess the hazard at local scales. Seismic microzonation maps provide the basis for scientifically based decision-making to reduce earthquake risk for Govt./public agencies, private owners and the general public. Further, seismic microzonation carried out on an appropriate scale provides a valuable tool for disaster mitigation planning and emergency response planning for urban centers / municipalities. It provides the basis for the identification of the areas of the city / municipality which are most likely to experience serious damage in the event of an earthquake.

Link route pricing for enhanced QoS

Pricing is an effective tool to control congestion and achieve quality of service (QoS) provisioning for multiple differentiated levels of service. In this paper, we consider the problem of pricing for congestion control in the case of a network of nodes under multiple service classes. Our work draws upon [1] and [2] in various ways. We use the Tirupati pricing scheme in conjunction with the stochastic approximation based adaptive pricing methodology for queue control (proposed in [1]) for minimizing network congestion. However, unlike the methodology of [1] where pricing for entire routes is directly considered, we consider prices for individual link-service grade tuples. Further, we adapt the methodology proposed in [21 for a single-node scenario to the case of a network of nodes, for evaluating performance in terms of price, revenue rate and disutility. We obtain considerable performance improvements using our approach over that in [1]. In particular, our approach exhibits a throughput improvement in the range of 54 to 80 percent in all cases studied (over all routes) while exhibiting a lower packet delay in the range of 26 to 38 percent over the scheme in [1].

Deploy and search strategy for multi-agent systems using Voronoi partitions

In this paper we analyze a deploy and search strategy for multi-agent systems. Mobile agents equipped with sensors carry out search operation in the search space. The lack of information about the search space is modeled as an uncertainty density distribution over the space, and is assumed to be known to the agents a priori. In each step, the agents deploy themselves in an optimal way so as to maximize per step reduction in the uncertainty density. We analyze the proposed strategy for convergence and spatial distributedness. The control law moving the agents has been analyzed for stability and convergence using LaSalle's invariance principle, and for spatial distributedness under a few realistic constraints on the control input such as constant speed, limit on maximum speed, and also sensor range limits. The simulation experiments show that the strategy successfully reduces the average uncertainty density below the required level.

Design of an optimal auction for sponsored search auctions

In this paper we first describe a framework to model the sponsored search auction on the web as a mechanism design problem. Using this framework, we design a novel auction which we call the OPT (optimal) auction. The OPT mechanism maximizes the search engine's expected revenue while achieving Bayesian incentive compatibility and individual rationality of the advertisers. We show that the OPT mechanism is superior to two of the most commonly used mechanisms for sponsored search namely (1) GSP (Generalized Second Price) and (2) VCG (Vickrey-Clarke-Groves). We then show an important revenue equivalence result that the expected revenue earned by the search engine is the same for all the three mechanisms provided the advertisers are symmetric and the number of sponsored slots is strictly less than the number of advertisers.

Quantitation and characterization of glutathionyl haemoglobin as an oxidative stress marker in chronic renal failure by mass spectrometry

Objectives: Glutathionyl haemoglobin (GS-Hb) belonging to the class of glutathionylated proteins has been investigated as a possible marker of oxidative stress in different chronic diseases. The purpose of this study was to examine whether glutathionyl haemoglobin can serve as an oxidative stress marker in non-diabetic chronic renal failure patients on different renal replacement therapies (RRT) through its quantitation, and characterization of the specific binding site of glutathione in haemoglobin molecule by mass spectrometric analysis. Design and methods: The study group consisted of non-diabetic chronic renal failure patients on renal replacement therapy (RRT): hemodialysis (HD), continuous ambulatory peritoneal dialysis (CAPD) and renal allograft transplant (Txp) patients. Haemoglobin samples of these subjects were analyzed by liquid chromatography electrospray ionization mass spectrometry for GS-Hb quantitation. Characterization of GS-Hb was done by tandem mass spectrometry. Levels of erythrocyte glutathione (GSH) and lipid peroxidation (as thiobarbituric acid reacting substances) were measured spectrophotometrically, while glycated baernoglobin (HbA1c) was measured by HPLC. Results: GS-Hb levels were markedly elevated in the dialysis group and marginally in the transplant group as compared to the controls. GS-Hb levels correlated positively with lipid peroxidation and negatively with the erythrocyte glutathione levels in RRT groups indicating enhanced oxidative stress. De novo sequencing of the chymotryptic fragment of GS-Hb established that glutathione is attached to Cys-93 of the beta globin chain. Mass spectrometric quantitation of total glycated haemoglobin showed good agreement with HbA1c estimation by conventional HPLC method. Conclusions: Glutathionyl haemoglobin can serve as a clinical marker of oxidative stress in chronic debilitating therapies like RRT. Mass spectrometry provides a reliable analytical tool for quantitation and residue level characterization of different post-translational modifications of haemoglobin. (c) 2007 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.

Self-interrupted regenerative metal cutting in turning

A new approach is used to study the global dynamics of regenerative metal cutting in turning. The cut surface is modeled using a partial differential equation (PDE) coupled, via boundary conditions, to an ordinary differential equation (ODE) modeling the dynamics of the cutting tool. This approach automatically incorporates the multiple-regenerative effects accompanying self-interrupted cutting. Taylor's 3/4 power law model for the cutting force is adopted. Lower dimensional ODE approximations are obtained for the combined tool–workpiece model using Galerkin projections, and a bifurcation diagram computed. The unstable solution branch off the subcritical Hopf bifurcation meets the stable branch involving self-interrupted dynamics in a turning point bifurcation. The tool displacement at that turning point is estimated, which helps identify cutting parameter ranges where loss of stability leads to much larger self-interrupted motions than in some other ranges. Numerical bounds are also obtained on the parameter values which guarantee global stability of steady-state cutting, i.e., parameter values for which there exist neither unstable periodic motions nor self-interrupted motions about the stable equilibrium.

Formal Verification of Full-Wave Rectifier: A Case Study

We present a case study of formal verification of full-wave rectifier for analog and mixed signal designs. We have used the Checkmate tool from CMU [1], which is a public domain formal verification tool for hybrid systems. Due to the restriction imposed by Checkmate it necessitates to make the changes in the Checkmate implementation to implement the complex and non-linear system. Full-wave rectifier has been implemented by using the Checkmate custom blocks and the Simulink blocks from MATLAB from Math works. After establishing the required changes in the Checkmate implementation we are able to efficiently verify, the safety properties of the full-wave rectifier.

Rotorcraft parameter estimation using radial basis function neural network

Increased emphasis on rotorcraft performance and perational capabilities has resulted in accurate computation of aerodynamic stability and control parameters. System identification is one such tool in which the model structure and parameters such as aerodynamic stability and control derivatives are derived. In the present work, the rotorcraft aerodynamic parameters are computed using radial basis function neural networks (RBFN) in the presence of both state and measurement noise. The effect of presence of outliers in the data is also considered. RBFN is found to give superior results compared to finite difference derivatives for noisy data. (C) 2010 Elsevier Inc. All rights reserved.