Machine-tool selection and operation allocation in FMS: solving a fuzzy goal-programming model using a genetic algorithm

The decision-making process for machine-tool selection and operation allocation in a flexible manufacturing system (FMS) usually involves multiple conflicting objectives. Thus, a fuzzy goal-programming model can be effectively applied to this decision problem. The paper addresses application of a fuzzy goal-programming concept to model the problem of machine-tool selection and operation allocation with explicit considerations given to objectives of minimizing the total cost of machining operation, material handling and set-up. The constraints pertaining to the capacity of machines, tool magazine and tool life are included in the model. A genetic algorithm (GA)-based approach is adopted to optimize this fuzzy goal-programming model. An illustrative example is provided and some results of computational experiments are reported.

Studies on a new high-intensity low-emission burner

This paper presents computational and experimental results on a new burner configuration with a mild combustion concept with heat release rates up to 10 MW/m(3). The burner configuration is shown to achieve mild combustion by using air at ambient temperature at high recirculation rates (similar to250%-290%) both experimentally and computationally. The principal features of the configuration are: (1) a burner with forward exit for exhaust gases; (2) injection of gaseous fuel and air as multiple, alternate, peripheral highspeed jets at the bottom at ambient temperature, thus creating high enough recirculation rates of the hot combustion products into fresh incoming reactants; and (3) use of a suitable geometric artifice-a frustum of a cone to help recirculation. The computational studies have been used to reveal the details of the flow and to optimize the combustor geometry based on recirculation rates. Measures, involving root mean square temperature fluctuations, distribution of temperature and oxidizer concentration inside the proposed burner, and a classical turbulent diffusion jet flame, are used to distinguish between them quantitatively. The system, operated at heat release rates of 2 to 10 MW/m(3) (compared to 0.02 to 0.32 MW/m(3) in the earlier studies), shows a 10-15 dB reduction in noise in the mild combustion mode compared to a simple open-top burner and exhaust NOx emission below 10 ppm for a 3 kW burner with 10% excess air. The peak temperature is measured around 1750 K, approximately 300 K lower than the peak temperature in a conventional burner.

An Adaptive Feature Based Low Power Motion Estimation Algorithm

Motion Estimation is one of the most power hungry operations in video coding. While optimal search (eg. full search)methods give best quality, non optimal methods are often used in order to reduce cost and power. Various algorithms have been used in practice that trade off quality vs. complexity. Global elimination is an algorithm based on pixel averaging to reduce complexity of motion search while keeping performance close to that of full search. We propose an adaptive version of the global elimination algorithm that extracts individual macro-block features using Hadamard transform to optimize the search. Performance achieved is close to the full search method and global elimination. Operational complexity and hence power is reduced by 30% to 45% compared to global elimination method.

Structured Learning for Non-Smooth Ranking losses

Learning to rank from relevance judgment is an active research area. Itemwise score regression, pairwise preference satisfaction, and listwise structured learning are the major techniques in use. Listwise structured learning has been applied recently to optimize important non-decomposable ranking criteria like AUC (area under ROC curve) and MAP(mean average precision). We propose new, almost-lineartime algorithms to optimize for two other criteria widely used to evaluate search systems: MRR (mean reciprocal rank) and NDCG (normalized discounted cumulative gain)in the max-margin structured learning framework. We also demonstrate that, for different ranking criteria, one may need to use different feature maps. Search applications should not be optimized in favor of a single criterion, because they need to cater to a variety of queries. E.g., MRR is best for navigational queries, while NDCG is best for informational queries. A key contribution of this paper is to fold multiple ranking loss functions into a multi-criteria max-margin optimization.The result is a single, robust ranking model that is close to the best accuracy of learners trained on individual criteria. In fact, experiments over the popular LETOR and TREC data sets show that, contrary to conventional wisdom, a test criterion is often not best served by training with the same individual criterion.

Search on a Hypercubic Lattice using Quantum Random Walk

We investigate the spatial search problem on the two-dimensional square lattice, using the Dirac evolution operator discretized according to the staggered lattice fermion formalism. d=2 is the critical dimension for the spatial search problem, where infrared divergence of the evolution operator leads to logarithmic factors in the scaling behavior. As a result, the construction used in our accompanying article [ A. Patel and M. A. Rahaman Phys. Rev. A 82 032330 (2010)] provides an O(√NlnN) algorithm, which is not optimal. The scaling behavior can be improved to O(√NlnN) by cleverly controlling the massless Dirac evolution operator by an ancilla qubit, as proposed by Tulsi Phys. Rev. A 78 012310 (2008). We reinterpret the ancilla control as introduction of an effective mass at the marked vertex, and optimize the proportionality constants of the scaling behavior of the algorithm by numerically tuning the parameters.

Energy-Efficient Decentralized Routing with Localized Cooperation Suitable for Fast Fading

Wireless networks transmit information from a source to a destination via multiple hops in order to save energy and, thus, increase the lifetime of battery-operated nodes. The energy savings can be especially significant in cooperative transmission schemes, where several nodes cooperate during one hop to forward the information to the next node along a route to the destination. Finding the best multi-hop transmission policy in such a network which determines nodes that are involved in each hop, is a very important problem, but also a very difficult one especially when the physical wireless channel behavior is to be accounted for and exploited. We model the above optimization problem for randomly fading channels as a decentralized control problem – the channel observations available at each node define the information structure, while the control policy is defined by the power and phase of the signal transmitted by each node.In particular, we consider the problem of computing an energy-optimal cooperative transmission scheme in a wireless network for two different channel fading models: (i) slow fading channels, where the channel gains of the links remain the same for a large number of transmissions, and (ii) fast fading channels,where the channel gains of the links change quickly from one transmission to another. For slow fading, we consider a factored class of policies (corresponding to local cooperation between nodes), and show that the computation of an optimal policy in this class is equivalent to a shortest path computation on an induced graph, whose edge costs can be computed in a decentralized manner using only locally available channel state information(CSI). For fast fading, both CSI acquisition and data transmission consume energy. Hence, we need to jointly optimize over both these; we cast this optimization problem as a large stochastic optimization problem. We then jointly optimize over a set of CSI functions of the local channel states, and a corresponding factored class of control policies corresponding to local cooperation between nodes with a local outage constraint. The resulting optimal scheme in this class can again be computed efficiently in a decentralized manner. We demonstrate significant energy savings for both slow and fast fading channels through numerical simulations of randomly distributed networks.

The Role of Tool Design in Influencing the Mechanism for the Formation of Friction Stir Welds in Aluminum Alloy 7020

Design of the required tool is a key and important parameter in the technique of friction stir welding (FSW). This is so because tool design does exert a close control over the quality of the weld. In an attempt to optimize tool design and its selection, it is essential and desirable to understand the mechanisms governing the formation of the weld. In this research study, few experiments were conducted to systematically analyze the intrinsic mechanisms governing the formation of the weld and to effectively utilize the analysis to establish a logical basis for design of the tool. For this purpose, the experiments were conducted using different geometries of the shoulder and pin of the rotating tool in such a way that only tool geometry had an intrinsic influence on formation of the weld. The results revealed that for a particular diameter of the pin there is an optimum diameter of the shoulder. Below this optimum shoulder diameter, the weld does not form while above the optimum diameter the overall symmetry of the weld is lost. Based on experimental results, a mechanism for the formation of friction stir weld is proposed. A synergism of the experimental results with the proposed mechanism is helpful in establishing the set of welding parameters for a given material.

Interdiffusion and Growth of the Phases in CoNi/Mo and CoNi/W Systems

Deleterious topological-closed-packed (tcp) phases grow in the interdiffusion zone in turbine blades mainly because of the addition of refractory elements such as Mo and W in the Ni- and Co-based superalloys. CoNi/Mo and CoNi/W diffusion couples are prepared to understand the growth mechanism of the phases in the interdiffusion zone. Instead of determining the main and cross-interdiffusion coefficients following the conventional method, we preferred to determine the average effective interdiffusion coefficients of two elements after fixing the composition of one element more or less the same in the interdiffusion zone. These parameters can be directly related to the growth kinetics of the phases and shed light on the atomic mechanism of diffusion. In both systems, the diffusion rate of elements and the phase layer thickness increased because of the addition of Ni in the solid solution phase, probably because of an increase in driving force. On the other hand, the growth rate of the mu phase and the diffusion coefficient of the species decreased because of the addition of Ni. This indicates the change in defect concentration, which assists diffusion. Further, we revisited the previously published Co-Ni-Mo and Co-Ni-W ternary phase diagrams and compared them with the composition range of the phases developed in the interdiffusion zone. Different composition ranges of the tcp phases are found, and corrected phase diagrams are shown. The outcome of this study will help to optimize the concentration of elements in superalloys to control the growth of the tcp phases.

Optimization of vibrating structures to reduce radiated noise

In this work, we propose an approach for reducing radiated noise from `light' fluid-loaded structures, such as, for example, vibrating structures in air. In this approach, we optimize the structure so as to minimize the dynamic compliance (defined as the input power) of the structure. We show that minimizing the dynamic compliance results in substantial reductions in the radiated sound power from the structure. The main advantage of this approach is that the redesign to minimize the dynamic compliance moves the natural frequencies of the structure away from the driving frequency thereby reducing the vibration levels of the structure, which in turn results in a reduction in the radiated sound power as an indirect benefit. Thus, the need for an acoustic and the associated sensitivity analysis is completely bypassed (although, in this work, we do carry out an acoustic analysis to demonstrate the reduction in sound power levels), making the strategy efficient compared to existing strategies in the literature which try to minimize some measure of noise directly. We show the effectiveness of the proposed approach by means of several examples involving both topology and stiffener optimization, for vibrating beam, plate and shell-type structures.

PAMAM Dendrimer-Drug Interactions: Effect of pH on the Binding and Release Pattern

Understanding the dendrimer-drug interaction is of great importance to design and optimize the dendrimer-based drug delivery system. Using atomistic molecular dynamics (MD) simulations, we have analyzed the release pattern of four ligands (two soluble drugs, namely, salicylic acid (Sal), L-alanine (Ala), and two insoluble drugs, namely, phenylbutazone (Pbz) and primidone (Prim)), which were initially encapsulated inside the ethylenediamine (EDA) cored polyamidoamine (PAMAM) dendrimer using the docking method. We have computed the potential of mean force (PMF) variation with generation 5 (G5)-PAMAM dendrimer complexed with drug molecules using umbrella sampling. From our calculated PMF values, we observe that soluble drugs (Sal and Ala) have lower energy barriers than insoluble drugs (Pbz and Prim). The order of ease of release pattern for these drugs from G5 protonated PAMAM dendrimer was found to be Ala > Sal > Prim > Pbz. In the case of insoluble drugs (Prim and Pbz), because of larger size, we observe much nonpolar contribution, and thus, their larger energy barriers can be reasoned to van der Waals contribution. From the hydrogen bonding analysis of the four PAMAM drug complexes under study, we found intermolecular hydrogen bonding to show less significant contribution to the free energy barrier. Another interesting feature appears while calculating the PMF profile of G5NP (nonprotonated)-PAMAM Pbz and G5NP (nonprotonated)-PAMAM-Sal complex. The PMF was found to be less when the drug is bound to nonprotonated dendrimer compared to the protonated dendrimer. Our results suggest that encapsulation of the drug molecule into the host PAMAM dendrimer should be carried out at higher pH values (near pH 10). When such complex enters the human body, the pH is around 7.4 and at that physiological pH, the dendrimer holds the drug tightly. Hence the release of drug can occur at a controlled rate into the bloodstream. Thus, our findings provide a microscopic picture of the encapsulation and controlled release of drugs in the case of dendrimer-based host-guest systems.

Dual-Stage Power Management Algorithms for Energy Harvesting Sensors

In this paper, we propose power management algorithms for maximizing the utility of energy harvesting sensors (EHS) that operate purely on the basis of energy harvested from the environment. In particular, we consider communication (i.e., transmission and reception) power management issues for EHS under an energy neutrality constraint. We also consider the fixed power loss effects of the circuitry, the battery inefficiency and its storage capacity, in the design of the algorithms. We propose a two-stage structure that exploits the inherent difference in the timescales at which the energy harvesting and channel fading processes evolve, without loss of optimality of the resulting solution. The outer stage schedules the power that can be used by an inner stage algorithm, so as to maximize the long term average utility and at the same time maintain energy neutrality. The inner stage optimizes the communication parameters to achieve maximum utility in the short-term, subject to the power constraint imposed by the outer stage. We optimize the algorithms for different transmission schemes such as the truncated channel inversion and retransmission strategies. The performance of the algorithms is illustrated via simulations using solar irradiance data, and for the case of Rayleigh fading channels. The results demonstrate the significant performance benefits that can be obtained using the proposed power management algorithms compared to the energy efficient (optimum when there is no storage) and the uniform power consumption (optimum when the battery has infinite capacity and is perfectly efficient) approaches.

About the transparent electrode of the organic photovoltaic cells

Electrodes and the nature of their contact with organic materials play a crucial role in the realization of efficient optoelectronic components. Whether the injection (organic light-emitting diodes - OLEDs) or collection (organic photovoltaic cells - OPV cells) of carriers, contacts must be as efficient as possible. To do this, it is customary to refer to electrode surface treatment and/or using a buffer layer all things to optimize the contact. Efficiency of organic photovoltaic cells based on organic electron donor/organic electron acceptor junctions can be strongly improved when the transparent conductive anode is coated with a buffer layer (ABL). We show that an ultra-thin gold (0.5 nm) or a thin molybdenum oxide (3-5 nm) can be used as efficient ABL. However, the effects of these ABL depend on the highest occupied molecular orbital (HOMO) of different electron donors of the OPV cells. The results indicate that, in the case of metal ABL, a good matching between the work function of the anode and the highest occupied molecular orbital of the donor material is the major factor limiting the hole transfer efficiency. Indeed, gold is efficient as ABL only when the HOMO of the organic donor is close to its work function Phi(Au). MoO3 has a wider field of application as ABL than gold. The role of the oxide is not so clearly understood than that of Au, different models proposed to interpret the experimental results are discussed.

Simple coating technique for 2-dimensional zinc oxide nanostructure

We report a novel and simple solution-based technique for depositing 2-D zinc oxide platelets at low temperature. Nanoplatelets that were mostly a-oriented associated with the Lotgering orientation factor of 0.65 were obtained by locating a glass substrate at a distance of about 5cm over the aqueous vapour of the boiling precursor. Experiments were carried out to optimize the coating parameters by placing the substrate at different positions, durations and the pH of the precursor. The X-ray diffraction studies confirmed the structure associated with the crystallites to be wurzite. The different morphology of the zinc oxide films and blue light emission were observed using scanning electron microscopy and fluorescence spectroscopy respectively.

Thermal degradation kinetics of poly(trimethylol propane triacrylate)/poly(hexane diol diacrylate) interpenetrating polymer network

Interpenetrating polymer networks (IPNs) of trimethylol propane triacrylate (TMPTA) and 1,6-hexane diol diacrylate (HDDA) at different weight ratios were synthesized. Temperature modulated differential scanning calorimetry (TMDSC) was used to determine whether the formation resulted in a copolymer or interpenetrating polymer network (IPN). These polymers are used as binders for microstereolithography (MSL) based ceramic microfabrication. The kinetics of thermal degradation of these polymers are important to optimize the debinding process for fabricating 3D shaped ceramic objects by MSL based rapid prototyping technique. Therefore, thermal and thermo-oxidative degradation of these IPNs have been studied by dynamic and isothermal thermogravimetry (TGA). Non-isothermal model-free kinetic methods have been adopted (isoconversional differential and KAS) to calculate the apparent activation energy (E a) as a function of conversion (α) in N 2 and air. The degradation of these polymers in N 2 atmosphere occurs via two mechanisms. Chain end scission plays a dominant role at lower temperature while the kinetics is governed by random chain scission at higher temperature. Oxidative degradation shows multiple degradation steps having higher activation energy than in N 2. Isothermal degradation was also carried out to predict the reaction model which is found to be decelerating. It was shown that the degradation of PTMPTA follows a contracting sphere reaction model in N 2. However, as the HDDA content increases in the IPNs, the degradation reaction follows Avrami-Erofeev model and diffusion governed mechanisms. The intermediate IPN compositions show both type of mechanism. Based on the above study, debinding strategy for MSL based microfabricated ceramic structure has been proposed. © 2012 Elsevier B.V.

Data-resolution based optimization of the data-collection strategy for near infrared diffuse optical tomography

Purpose: To optimize the data-collection strategy for diffuse optical tomography and to obtain a set of independent measurements among the total measurements using the model based data-resolution matrix characteristics. Methods: The data-resolution matrix is computed based on the sensitivity matrix and the regularization scheme used in the reconstruction procedure by matching the predicted data with the actual one. The diagonal values of data-resolution matrix show the importance of a particular measurement and the magnitude of off-diagonal entries shows the dependence among measurements. Based on the closeness of diagonal value magnitude to off-diagonal entries, the independent measurements choice is made. The reconstruction results obtained using all measurements were compared to the ones obtained using only independent measurements in both numerical and experimental phantom cases. The traditional singular value analysis was also performed to compare the results obtained using the proposed method. Results: The results indicate that choosing only independent measurements based on data-resolution matrix characteristics for the image reconstruction does not compromise the reconstructed image quality significantly, in turn reduces the data-collection time associated with the procedure. When the same number of measurements (equivalent to independent ones) are chosen at random, the reconstruction results were having poor quality with major boundary artifacts. The number of independent measurements obtained using data-resolution matrix analysis is much higher compared to that obtained using the singular value analysis. Conclusions: The data-resolution matrix analysis is able to provide the high level of optimization needed for effective data-collection in diffuse optical imaging. The analysis itself is independent of noise characteristics in the data, resulting in an universal framework to characterize and optimize a given data-collection strategy. (C) 2012 American Association of Physicists in Medicine. http://dx.doi.org/10.1118/1.4736820]