A self-adaptive migration model genetic algorithm for data mining applications

Data mining involves nontrivial process of extracting knowledge or patterns from large databases. Genetic Algorithms are efficient and robust searching and optimization methods that are used in data mining. In this paper we propose a Self-Adaptive Migration Model GA (SAMGA), where parameters of population size, the number of points of crossover and mutation rate for each population are adaptively fixed. Further, the migration of individuals between populations is decided dynamically. This paper gives a mathematical schema analysis of the method stating and showing that the algorithm exploits previously discovered knowledge for a more focused and concentrated search of heuristically high yielding regions while simultaneously performing a highly explorative search on the other regions of the search space. The effective performance of the algorithm is then shown using standard testbed functions and a set of actual classification datamining problems. Michigan style of classifier was used to build the classifier and the system was tested with machine learning databases of Pima Indian Diabetes database, Wisconsin Breast Cancer database and few others. The performance of our algorithm is better than others.

A Deterministic Optimization Approach to Protein Sequence Design Using Continuous Models

Determining the sequence of amino acid residues in a heteropolymer chain of a protein with a given conformation is a discrete combinatorial problem that is not generally amenable for gradient-based continuous optimization algorithms. In this paper we present a new approach to this problem using continuous models. In this modeling, continuous "state functions" are proposed to designate the type of each residue in the chain. Such a continuous model helps define a continuous sequence space in which a chosen criterion is optimized to find the most appropriate sequence. Searching a continuous sequence space using a deterministic optimization algorithm makes it possible to find the optimal sequences with much less computation than many other approaches. The computational efficiency of this method is further improved by combining it with a graph spectral method, which explicitly takes into account the topology of the desired conformation and also helps make the combined method more robust. The continuous modeling used here appears to have additional advantages in mimicking the folding pathways and in creating the energy landscapes that help find sequences with high stability and kinetic accessibility. To illustrate the new approach, a widely used simplifying assumption is made by considering only two types of residues: hydrophobic (H) and polar (P). Self-avoiding compact lattice models are used to validate the method with known results in the literature and data that can be practically obtained by exhaustive enumeration on a desktop computer. We also present examples of sequence design for the HP models of some real proteins, which are solved in less than five minutes on a single-processor desktop computer Some open issues and future extensions are noted.

Variational Asymptotic Analysis of a Self-healing SMA Composite

A Shape Memory Alloy (SMA) wire reinforced composite shell structure is analyzed for self-healing characteristic using Variational Asymptotic Method (VAM). SMA behavior is modeled using a onedimensional constitutive model. A pre-notched specimen is loaded longitudinally to simulate crack propagation. The loading process is accompanied by martensitic phase transformation in pre-strained SMA wires, bridging the crack. To heal the composite, uniform heating is required to initiate reverse transformation in the wires and bringing the crack faces back into contact. The pre-strain in the SMA wires used for reinforcement, causes a closure force across the crack during reverse transformation of the wires under heating. The simulation can be useful in design of self-healing composite structures using SMA. Effect of various parameters, like composite and SMA material properties and the geometry of the specimen, on the cracking and self-healing can also be studied.

Self-Assembly of Metallamacrocycles Using a Dinuclear Organometallic Acceptor: Synthesis, Characterization, and Sensing Study

A dinuclear organometallic acceptor 4,4'-bis[trans-Pt(PEt(3))(2)(O(3)SCF(3))(ethynyl)]biphenyl (1) containing Pt-ethynyl functionality is synthesized. Multinuclear NMR ((1)H, (31)P, and (13)C), infrared (IR), and electrospray ionization mass spectrometry (ESI-MS) including single-crystal X-ray diffraction analysis established the formation of 1. Equimolar treatment of acceptor 1 separately with three different ``clip'' type ditopic donors (L(a)-L(c)) yielded [2 + 2] self-assembled three metallamacrocycles 2a-2c, respectively. These macrocycles were characterized by various spectroscopic techniques, and their sizes/shapes were obtained through geometry optimization using molecular mechanics universal force field (MMUFF) simulations. Attachment of unsaturated ethynyl functionality to biphenyl building unit helped to make the macrocycles (2a-2c) pi-electron rich and thereby fluorescent in nature. Furthermore, 2c in solution has been examined to be suitable for sensing electron-deficient nitroaromatic like picric acid, which is often considered as a secondary chemical explosive. The fluorescence study of 2c showed a marked quenching of initial emission intensity upon titrating with picric acid (PA), and it exhibited the largest fluorescence quenching response with high selectivity among various other electron deficient aromatic compounds tested.

Freeform Skeletal Shape Optimization of Compliant Mechanisms

Compliant mechanisms are elastic continua used to transmit or transform force and motion mechanically. The topology optimization methods developed for compliant mechanisms also give the shape for a chosen parameterization of the design domain with a fixed mesh. However, in these methods, the shapes of the flexible segments in the resulting optimal solutions are restricted either by the type or the resolution of the design parameterization. This limitation is overcome in this paper by focusing on optimizing the skeletal shape of the compliant segments in a given topology. It is accomplished by identifying such segments in the topology and representing them using Bezier curves. The vertices of the Bezier control polygon are used to parameterize the shape-design space. Uniform parameter steps of the Bezier curves naturally enable adaptive finite element discretization of the segments as their shapes change. Practical constraints such as avoiding intersections with other segments, self-intersections, and restrictions on the available space and material, are incorporated into the formulation. A multi-criteria function from our prior work is used as the objective. Analytical sensitivity analysis for the objective and constraints is presented and is used in the numerical optimization. Examples are included to illustrate the shape optimization method.

Self-Assembled, Aligned ZnO Nanorod Buffer Layers for High-Current-Density, Inverted Organic Photovoltaics

Two different soft-chemical, self-assembly-based solution approaches are employed to grow zinc oxide (ZnO) nanorods with controlled texture. The methods used involve seeding and growth on a substrate. Nanorods with various aspect ratios (1-5) and diameters (15-65 nm) are grown. Obtaining highly oriented rods is determined by the way the substrate is mounted within the chemical bath. Furthermore, a preheat and centrifugation step is essential for the optimization of the growth solution. In the best samples, we obtain ZnO nanorods that are almost entirely oriented in the (002) direction; this is desirable since electron mobility of ZnO is highest along this crystallographic axis. When used as the buffer layer of inverted organic photovoltaics (I-OPVs), these one-dimensional (1D) nanostructures offer: (a) direct paths for charge transport and (b) high interfacial area for electron collection. The morphological, structural, and optical properties of ZnO nanorods are studied using scanning electron microscopy, X-ray diffraction, and ultraviolet-visible light (UV-vis) absorption spectroscopy. Furthermore, the surface chemical features of ZnO films are studied using X-ray photoelectron spectroscopy and contact angle measurements. Using as-grown ZnO, inverted OPVs are fabricated and characterized. For improving device performance, the ZnO nanorods are subjected to UV-ozone irradiation. UV-ozone treated ZnO nanorods show: (i) improvement in optical transmission, (ii) increased wetting of active organic components, and (iii) increased concentration of Zn-O surface bonds. These observations correlate well with improved device performance. The devices fabricated using these optimized buffer layers have an efficiency of similar to 3.2% and a fill factor of 0.50; this is comparable to the best I-OPVs reported that use a P3HT-PCBM active layer.

Self-assembly of Metallamacrocycles Employing a New Benzil-based Organometallic Bisplatinum(II) Acceptor

A benzil-based semi-rigid dinuclear organometallic acceptor 4,4'-bistrans-Pt(PEt3)(2)(NO3)(ethynyl)]benzil (bisPt-NO3) containing a Pt-ethynyl functionality was synthesized in good yield and characterized by multinuclear NMR (H-1, P-31, and C-13), electrospray ionization mass spectrometry (ESI-MS), and single-crystal X-ray diffraction analysis of the iodide analogue bisPt-I. The stoichiometric (1:1) combination of the acceptor bisPt-NO3 separately with four different ditopic donors (L-1-L-4; L-1 = 9-ethyl-3,6-di(1H-imidazol-1-yl)-9H-carbazole, L-2 = 1,4-bis((1H-imidazol-1-yl)methyl)benzene, L-3 = 1,3-bis((1H-imidazol-1-yl)methyl)benzene and L-4 = 9,10-bis((1H-imidazol-1-yl) methyl)anthracene) yielded four 2 + 2] self-assembled metallacycles M-1-M-4 in quantitative yields, respectively. All these newly synthesized assemblies were characterized by various spectroscopic techniques (NMR, IR, ESI-MS) and their sizes/shapes were predicted through geometry optimization employing the PM6 semi-empirical method. The benzil moiety was introduced in the backbone of the acceptor bisPt-NO3 due to the interesting structural feature of long carbonyl C-C bond (similar to 1.54 angstrom), which enabled us to probe the role of conformational flexibility on size and shapes of the resulting coordination ensembles.

Template-free coordination-driven self-assembly of discrete hexanuclear prismatic cages employing half-sandwich octahedral Ru-2(II) acceptors and triimidazole donors

Coordination-driven self-assembly of dinuclear half-sandwich p-cymene ruthenium(II) complexes Ru-2(mu-eta(4)-C2O4)(CH3OH)(2)(eta(6)-p-cymene)(2)](O3SCF3)(2) (1a) and Ru-2(mu-eta(4)-C6H2O4)(CH3OH)(2)(eta(6)-p-cymene)(2)](O3SCF3)(2) (1b) separately with imidazole-based tritopic donors (L-1-L-2) in methanol yielded a series of hexanuclear 3+2] trigonal prismatic cages (2-5), respectively L-1 = 1,3,5-tris(imidazole-1-yl) benzene; L-2 = 4,4',4 `'-tris(imidazole-1-yl) triphenylamine]. All the self-assembled cages 2-5 were characterized by various spectroscopic techniques (multinuclear NMR, Infra-red and ESI-MS) and their sizes, shapes were obtained through geometry optimization using molecular mechanics universal force field (MMUFF) computation. Despite the possibility due to the free rotation of donor sites of imidazole ligands, of two different atropoisomeric prismatic cages (C-3h or C-s) and polymeric product, the self-selection of single (C(3)h) conformational isomeric cages as the only product is a noteworthy observation. (C) 2015 Elsevier B.V. All rights reserved.

Self-organized criticality in dynamics without branching

We demonstrate the phenomenon of self-organized criticality (SOC) in a simple random walk model described by a random walk of a myopic ant, i.e., a walker who can see only nearest neighbors. The ant acts on the underlying lattice aiming at uniform digging, i.e., reduction of the height profile of the surface but is unaffected by the underlying lattice. In one, two, and three dimensions we have explored this model and have obtained power laws in the time intervals between consecutive events of "digging." Being a simple random walk, the power laws in space translate to power laws in time. We also study the finite size scaling of asymptotic scale invariant process as well as dynamic scaling in this system. This model differs qualitatively from the cascade models of SOC.

Chiral molecular self-assembly of phospholipid tubules: A circular dichroism study

We report on spectroscopic studies of the chiral structure in phospholipid tubules formed in mixtures of alcohol and water. Synthetic phospholipids containing diacetylenic moieties in the acyl chains self-assemble into hollow, cylindrical tubules in appropriate conditions. Circular dichroism provides a direct measure of chirality of the molecular structure. We find that the CD spectra of tubules formed in mixtures of alcohol and water depends strongly on the alcohol used and the lipid concentration. The relative spectral intensity of different circular dichroism bands correlates with the number of bilayers observed using microscopy. The results provide experimental evidence that tubule formation is based on chiral packing of the lipid molecules and that interbilayer interactions are important to the tubule structure

Reservoir Operation for Hydropower Optimization: A Chance-Constrained Approach

This paper presents a chance-constrained linear programming formulation for reservoir operation of a multipurpose reservoir. The release policy is defined by a chance constraint that the probability of irrigation release in any period equalling or exceeding the irrigation demand is at least equal to a specified value P (called reliability level). The model determines the maximum annual hydropower produced while meeting the irrigation demand at a specified reliability level. The model considers variation in reservoir water level elevation and also the operating range within which the turbine operates. A linear approximation for nonlinear power production function is assumed and the solution obtained within a specified tolerance limit. The inflow into the reservoir is considered random. The chance constraint is converted into its deterministic equivalent using a linear decision rule and inflow probability distribution. The model application is demonstrated through a case study.

Self-Absorption and Focusing Effects in Carrier Relaxation Dynamics under Depletion Conditions

The effect of a one-dimensional field (1) on the self-absorption characteristics and (2) when we have a finite numerical aperture for the objective lens that focuses the laser beam on the solid are considered here. Self-absorption, in particular its manifestation as an inner filter for the emitted signal, has been observed in luminescence experiments. Models for this effect exist and have been analyzed, but only in the absence of space charge. Using our previous results on minority carrier relaxation in the presence of a field, we obtain expressions incorporating inner filter effects. Focusing of a light beam on the sample, by an objective lens, results in a three-dimensional source and consequently a three-dimensional continuity equation to be solved for the minority carrier concentration. Assuming a one-dimensional electric field and employing Fourier-Bessel transforms, we recast the problem of carrier relaxation and solve the same via an identity that relates it to solutions obtained in the absence of focusing effects. The inner filter effect as well as focusing introduces new time scales in the problem of carrier relaxation. The interplay between the electric field and the parameters which characterize these effects and the consequent modulation of the intensity and time scales of carrier decay signals are analyzed and discussed.

Fuzzy optimization model for water quality management of a river system - Closure

A fuzzy waste-load allocation model, FWLAM, is developed for water quality management of a river system using fuzzy multiple-objective optimization. An important feature of this model is its capability to incorporate the aspirations and conflicting objectives of the pollution control agency and dischargers. The vagueness associated with specifying the water quality criteria and fraction removal levels is modeled in a fuzzy framework. The goals related to the pollution control agency and dischargers are expressed as fuzzy sets. The membership functions of these fuzzy sets are considered to represent the variation of satisfaction levels of the pollution control agency and dischargers in attaining their respective goals. Two formulations—namely, the MAX-MIN and MAX-BIAS formulations—are proposed for FWLAM. The MAX-MIN formulation maximizes the minimum satisfaction level in the system. The MAX-BIAS formulation maximizes a bias measure, giving a solution that favors the dischargers. Maximization of the bias measure attempts to keep the satisfaction levels of the dischargers away from the minimum satisfaction level and that of the pollution control agency close to the minimum satisfaction level. Most of the conventional water quality management models use waste treatment cost curves that are uncertain and nonlinear. Unlike such models, FWLAM avoids the use of cost curves. Further, the model provides the flexibility for the pollution control agency and dischargers to specify their aspirations independently.

Exceptional adhesive and gelling properties of fibrous nanoscopic tapes of self-assembled bipolar urethane amides of L-phenylalanine

Seven L-phenylalanine based alkyl (monopolar) and alkanediyl (bipolar) derivatives are synthesized; while the bipolar urethane amides form gels and show strong adhesive properties, the monopolar analogues form fibrous nanoscopic cloth-like tapes.

A probabilistic constrained nonlinear optimization framework to optimize RED parameters

The random early detection (RED) technique has seen a lot of research over the years. However, the functional relationship between RED performance and its parameters viz,, queue weight (omega(q)), marking probability (max(p)), minimum threshold (min(th)) and maximum threshold (max(th)) is not analytically availa ble. In this paper, we formulate a probabilistic constrained optimization problem by assuming a nonlinear relationship between the RED average queue length and its parameters. This problem involves all the RED parameters as the variables of the optimization problem. We use the barrier and the penalty function approaches for its Solution. However (as above), the exact functional relationship between the barrier and penalty objective functions and the optimization variable is not known, but noisy samples of these are available for different parameter values. Thus, for obtaining the gradient and Hessian of the objective, we use certain recently developed simultaneous perturbation stochastic approximation (SPSA) based estimates of these. We propose two four-timescale stochastic approximation algorithms based oil certain modified second-order SPSA updates for finding the optimum RED parameters. We present the results of detailed simulation experiments conducted over different network topologies and network/traffic conditions/settings, comparing the performance of Our algorithms with variants of RED and a few other well known adaptive queue management (AQM) techniques discussed in the literature.