Generating artificial chromosomes with probability control in genetic algorithm for machine scheduling problems

In this paper, a novel genetic algorithm is developed by generating artificial chromosomes with probability control to solve the machine scheduling problems. Generating artificial chromosomes for Genetic Algorithm (ACGA) is closely related to Evolutionary Algorithms Based on Probabilistic Models (EAPM). The artificial chromosomes are generated by a probability model that extracts the gene information from current population. ACGA is considered as a hybrid algorithm because both the conventional genetic operators and a probability model are integrated. The ACGA proposed in this paper, further employs the ``evaporation concept'' applied in Ant Colony Optimization (ACO) to solve the permutation flowshop problem. The ``evaporation concept'' is used to reduce the effect of past experience and to explore new alternative solutions. In this paper, we propose three different methods for the probability of evaporation. This probability of evaporation is applied as soon as a job is assigned to a position in the permutation flowshop problem. Experimental results show that our ACGA with the evaporation concept gives better performance than some algorithms in the literature.

A Low-Complexity Algorithm for Intrusion Detection in a PIR-Based Wireless Sensor Network

We present a low-complexity algorithm for intrusion detection in the presence of clutter arising from wind-blown vegetation, using Passive Infra-Red (PIR) sensors in a Wireless Sensor Network (WSN). The algorithm is based on a combination of Haar Transform (HT) and Support-Vector-Machine (SVM) based training and was field tested in a network setting comprising of 15-20 sensing nodes. Also contained in this paper is a closed-form expression for the signal generated by an intruder moving at a constant velocity. It is shown how this expression can be exploited to determine the direction of motion information and the velocity of the intruder from the signals of three well-positioned sensors.

Two Novel Hexadepsipeptides with Several Modified Amino Acid Residues Isolated from the Fungus

Two new cyclohexadepsipeptides have been isolated from the fungus Isaria. Fungal growth in solid media yielded hyphal strands from which peptide fractions were readily isolable by organic-solvent extraction. Two novel cyclodepsipeptides, isaridin A and isaridin B, have been isolated by reverse-phase HPLC, and characterized by ESI-MS and 1H-NMR. Single crystals of both peptides have been obtained, and their 3D structures were elucidated by X-ray diffraction. The isaridins contain several unusual amino acid residues. The sequences are cyclo(β-Gly-HyLeu-Pro-Phe-NMeVal-NMePhe) and cyclo(β-Gly-HyLeu-β-MePro-Phe-NMeVal-NMePhe), where NMeVal is N-methylvaline, NMePhe N-methylphenylalanine, and HyLeu hydroxyleucine (=2-hydroxy-4-methylpentanoic acid). The two peptides differ from one another at residue 3, isaridin A having an (S)-proline at this position, while β-methyl-(S)-proline (=(2S,3S)-2,3,4,5-tetrahydro-3-methyl-1H-pyrrole-2-carboxylic acid) is found in isaridin B. The solid-state conformations of both cyclic depsipeptides are characterized by the presence of two cis peptide bonds at HyLeu(2)-Pro(3)/HyLeu(2)-β-MePro(3) and NMeVal(5)-NMePhe(6), respectively. In isaridin A, a strong intramolecular H-bond is observed between Phe(4)CO⋅⋅⋅HNβ-Gly(1), and a similar, but weaker, interaction is observed between β-Gly(1)CO⋅⋅⋅HNPhe(4). In contrast, in isaridin B, only a single intramolecular H-bond is observed between β-Gly(1)CO⋅⋅⋅HNPhe(4

Photocatalytic treatment of municipal wastewater using modified neodymium doped TiO2 hybrid nanoparticles

Photocatalytic degradation of municipal wastewater was investigated using reagent grade TiO2 and modified neodymium doped TiO2 hybrid nanoparticles. For the first time, surface modification of Nd3+ doped TiO2 hybrid nanoparticles were carried out with n-butylamine as surface modifier under mild hydrothermal conditions. The modified nanoparticles obtained were characterized by Powder XRD, FTIR, DLS, TEM, BET surface area, zeta potential and UV-Vis Spectroscopy. The characterization results indicated better morphology, particle size distribution and low agglomeration of the nanoparticles synthesized. It was found that photodegradation of wastewater using surface modified neodymium doped TiO2 nanoparticles was more compared to pure TiO2, which can be attributed to the doping and modification with n-butylamine.

A heuristic clustering algorithm using union of overlapping pattern-cells

Relative geometric arrangements of the sample points, with reference to the structure of the imbedding space, produce clusters. Hence, if each sample point is imagined to acquire a volume of a small M-cube (called pattern-cell), depending on the ranges of its (M) features and number (N) of samples; then overlapping pattern-cells would indicate naturally closer sample-points. A chain or blob of such overlapping cells would mean a cluster and separate clusters would not share a common pattern-cell between them. The conditions and an analytic method to find such an overlap are developed. A simple, intuitive, nonparametric clustering procedure, based on such overlapping pattern-cells is presented. It may be classified as an agglomerative, hierarchical, linkage-type clustering procedure. The algorithm is fast, requires low storage and can identify irregular clusters. Two extensions of the algorithm, to separate overlapping clusters and to estimate the nature of pattern distributions in the sample space, are also indicated.

On characterization of deformation microstructure in Boron modified Ti-6Al-4V alloy

Addition of boron in small quantities to various titanium alloys have shown significant improvement in mechanical behavior of materials. In the present study, electron back-scatter diffraction (EBSD) techniques have been applied to investigate the deformation microstructure evolution in boron modified two-phase titanium alloy Ti-6Al-4V. The alloy was hot compressed at 750 degrees C up to 50% height reduction at two different strain rates (10(-3) s(-1) and 1 s(-1)). The EBSD analyses indicated significant differences in deformed microstructure of the base alloy and the alloy containing boron. A strong subgrain formation tendency was observed along with inhomogeneous distribution of dislocations inside large a colonies of Ti64. In contrast, a colonies were relatively strain free for Ti64 + B, with more uniform dislocation density distribution. The observed difference is attributed to microstructural modifications viz, grain size refinement and presence of TiB particles at grain boundary produced due to boron addition. (C) 2010 Elsevier B.V. All rights reserved.

An efficient algorithm for linear programming

A simple but efficient algorithm is presented for linear programming. The algorithm computes the projection matrix exactly once throughout the computation unlike that of Karmarkar’s algorithm where in the projection matrix is computed at each and every iteration. The algorithm is best suitable to be implemented on a parallel architecture. Complexity of the algorithm is being studied.

A systolic algorithm for hidden surface removal

With the advent of VLSI it has become possible to map parallel algorithms for compute-bound problems directly on silicon. Systolic architecture is very good candidate for VLSI implementation because of its regular and simple design, and regular communication pattern. In this paper, a systolic algorithm and corresponding systolic architecture, a linear systolic array, for the scanline-based hidden surface removal problem in three-dimensional computer graphics have been proposed. The algorithm is based on the concept of sample spans or intervals. The worst case time taken by the algorithm is O(n), n being the number of segments in a scanline. The time taken by the algorithm for a given scene depends on the scene itself, and on an average considerable improvement over the worst case behaviour is expected. A pipeline scheme for handling the I/O process has also been proposed which is suitable for VLSI implementation of the algorithm.

Random-Restart Reactive Tabu Search Algorithm for Detection in Large-MIMO Systems

We present a low-complexity algorithm based on reactive tabu search (RTS) for near maximum likelihood (ML) detection in large-MIMO systems. The conventional RTS algorithm achieves near-ML performance for 4-QAM in large-MIMO systems. But its performance for higher-order QAM is far from ML performance. Here, we propose a random-restart RTS (R3TS) algorithm which achieves significantly better bit error rate (BER) performance compared to that of the conventional RTS algorithm in higher-order QAM. The key idea is to run multiple tabu searches, each search starting with a random initial vector and choosing the best among the resulting solution vectors. A criterion to limit the number of searches is also proposed. Computer simulations show that the R3TS algorithm achieves almost the ML performance in 16 x 16 V-BLAST MIMO system with 16-QAM and 64-QAM at significantly less complexities than the sphere decoder. Also, in a 32 x 32 V-BLAST MIMO system, the R3TS performs close to ML lower bound within 1.6 dB for 16-QAM (128 bps/Hz), and within 2.4 dB for 64-QAM (192 bps/Hz) at 10(-3) BER.

An efficient marching algorithm for waterhammer analysis by the method of characteristics

A new fast and efficient marching algorithm is introduced to solve the basic quasilinear, hyperbolic partial differential equations describing unsteady, flow in conduits by the method of characteristics. The details of the marching method are presented with an illustration of the waterhammer problem in a simple piping system both for friction and frictionless cases. It is shown that for the same accuracy the new marching method requires fewer computational steps, less computer memory and time.

An optimal parallel algorithm for sparse matrix bandwidth reduction on a linear array

A simple and efficient algorithm for the bandwidth reduction of sparse symmetric matrices is proposed. It involves column-row permutations and is well-suited to map onto the linear array topology of the SIMD architectures. The efficiency of the algorithm is compared with the other existing algorithms. The interconnectivity and the memory requirement of the linear array are discussed and the complexity of its layout area is derived. The parallel version of the algorithm mapped onto the linear array is then introduced and is explained with the help of an example. The optimality of the parallel algorithm is proved by deriving the time complexities of the algorithm on a single processor and the linear array.

Focal plane analysis of the Knox-Thompson algorithm in speckle interferometry

For the specific case of binary stars, this paper presents signal-to-noise ratio (SNR) calculations for the detection of the parity (the side of the brighter component) of the binary using the double correlation method. This double correlation method is a focal plane version of the well-known Knox-Thompson method used in speckle interferometry. It is shown that SNR for parity detection using double correlation depends linearly on binary separation. This new result was entirely missed by previous analytical calculations dealing with a point source. It is concluded that, for magnitudes relevant to the present day speckle interferometry and for binary separations close to the diffraction limit, speckle masking has better SNR for parity detection.

Error-free matrix symmetrizers and equivalent symmetric matrices

A symmetrizer of the matrix A is a symmetric solution X that satisfies the matrix equation XA=AprimeX. An exact matrix symmetrizer is computed by obtaining a general algorithm and superimposing a modified multiple modulus residue arithmetic on this algorithm. A procedure based on computing a symmetrizer to obtain a symmetric matrix, called here an equivalent symmetric matrix, whose eigenvalues are the same as those of a given real nonsymmetric matrix is presented.