Flow shop batching and scheduling with sequence-dependent setup times

This paper addresses the flow shop batching and scheduling problem where sequence-dependent family setup times are present and the objective is to minimize makespan. We consider violating the group technology assumption by dividing product families into batches. In order to reduce setup times, inconsistent batches are formed on different machines, which lead to non-permutation schedules. To the best of our knowledge, this is the first time that the splitting of job families into inconsistent batches has been considered in a flow shop system. A tabu search algorithm is developed which contains several neighbourhood functions, double tabu lists and a multilevel diversification structure. Compared to the state-of-the-art meta-heuristics for this problem, the proposed tabu search algorithm achieves further improvement when the group scheduling assumption is dropped. Also, various experiments conducted on the benchmark problem instances confirm the benefits of batching. Therefore, it will be prudent for the practitioners to consider adopting inconsistent batches and non-permutation schedules to improve their operational efficiency within a reasonable amount of computational effort.     

Crystallization of PP in PP/SEBS blends and its correlation with tensile properties

Crystallization of polypropylene (PP) in the blends of PP with styrene–ethylene butylene–styrene triblock copolymer (SEBS) is studied through differential thermal analysis (DTA) and X-ray diffraction measurements. Analysis of crystallization exotherm peaks in terms of crystallization nucleation and growth rates, crystallite size distribution, and crystallinity revealed differences in the morphology of PP component in the blend in the different regions of blend composition. Crystallinity determined by X-ray diffraction and DTA showed identical variations with blend composition. Variations in tensile properties of these blends with blend composition are also reported. Correlations of the various tensile properties with the crystallization parameters, viz., the crystallinity and crystallite size distribution, are presented, which confirm the influence of crystallization of PP component on the tensile properties of these blends.     

Numerical and experimental investigation of three-dimensional flow in extrusion dies

The univariant element, Q₁ P₀, and the multivariant elements, QP₀ and R P₀, are compared for the numerical simulation of the flow in extrusion dies. The pressure distribution obtained by using the Q₁ P₀ element was found to be afflicted with the checkerboard pressure mode. On the other hand, the multivariant elements, Q P₀ and R P₀, gave accurate and physically reasonable velocity and pressure distributions. The computed values of the pressure drop across extrusion dies matched well with the pressure drop determined experimentally.     

Random arithmetic formulas can be reconstructed efficiently

Informally stated, we present here a randomized algorithm that given black-box access to the polynomial f computed by an unknown/hidden arithmetic formula ? reconstructs, on the average, an equivalent or smaller formula \({\hat{\phi}}\) in time polynomial in the size of its output \({\hat{\phi}}\) . Specifically, we consider arithmetic formulas wherein the underlying tree is a complete binary tree, the leaf nodes are labeled by affine forms (i.e., degree one polynomials) over the input variables and where the internal nodes consist of alternating layers of addition and multiplication gates. We call these alternating normal form (ANF) formulas. If a polynomial f can be computed by an arithmetic formula μ of size s, it can also be computed by an ANF formula ?, possibly of slightly larger size s ^O(1). Our algorithm gets as input black-box access to the output polynomial f (i.e., for any point x in the domain, it can query the black box and obtain f(x) in one step) of a random ANF formula ? of size s (wherein the coefficients of the affine forms in the leaf nodes of ? are chosen independently and uniformly at random from a large enough subset of the underlying field). With high probability (over the choice of coefficients in the leaf nodes), the algorithm efficiently (i.e., in time s ^O(1)) computes an ANF formula \({\hat{\phi}}\) of size s computing f. This then is the strongest model of arithmetic computation for which a reconstruction algorithm is presently known, albeit efficient in a distributional sense rather than in the worst case.     

Aspects of the Softness and Hardness Concepts of Density-Functional Theory

In the density-functional theory of the ground state of an electronic system there arise the concepts of softness, hardness, local softness, and local hardness. Definitions of these quantities are reviewed, and then local softness and local hardness are discussed in some detail. The local softness of a species, the derivative , is a measure of the chemical reactivity of a site in the molecule. From it can be obtained the total global absolute softness in the sense of Pearson and a normalized chemical reactivity index of frontier type. Several formulas for s( r ) are obtained, including new fluctuation formulas, and its determinative role in chemisorption, catalysis, and frontier-controlled charge-transfer processes is briefly discussed. Local hardness is a corresponding appropriately defined functional derivative η(r) = [δμ/δp(r)]_v(r). Difficulties associated with ambiguities in this definition are discussed and resolved. It is concluded that for most purposes the best working formula for local hardness is , where η(r, r′) is the hardness kernel; , where F[p] is the usual Hohenberg-Kohn functional and f(r) is the Fukui function. With this definition, η(r) = η, a constant which is the global hardness. Just as the chemical potential equalizes in the ground state, so does the hardness. It is demonstrated that hardness can be taken to be an average of orbital contributions.     

An analysis of wet grinding operation using a linearized population balance model for a pilot scale grate-discharge ball mill

Batch and continuous wet grinding experiments were carried out in a 40 × 40 cm grate-discharge ball bill. Well-distributed ?4 and ?20 mesh feeds of two complex pyritic ores were used. The vol. % solids in the pulp ranged from 30 to 40, the particle load from 5 to 8 kg, and the solids feed rate from 70 to 110 kg/h.Analysis of the experimental data showed that over the range of operating conditions investigated, a linearized model could be used to predict the size distributions of both the mill product as well as the mill hold-up of the solids, very accurately. The breakage rate parameters, S_i, were found to be dependent on the mode of operation, independent of the percent solids in the pulp, and approximately inversely proportional to the mill hold-up weight of the solids. In the case of the continuous mode of operation, with decrease in particle size the rate parameter values became increasingly smaller by comparison with the corresponding expected batch operation values.     

Survey of denoising,segmentation and classification of magnetic resonance imaging for prostate cancer

Multimedia Tools and Applications - Prostate cancer (PCa) has become the second most dreadful cancer in men after lung cancer. Traditional approaches used for treatment of PCa were manual, time...     

A method for automatic classification of gender based on text- independent handwriting

Handwriting recognition is used for the prediction of various demographic traits such as age, gender, nationality, etc. Out of all the applications gender prediction is mainly admired topic among researchers. The relation between gender and handwriting can be seen from the physical appearance of the handwriting. This research work predicts gender from handwriting using the landmarks of differences between the two genders. We use the shape or visual appearance of the handwriting for extracting features of the handwriting such as slanteness (direction), area (no of pixels occupied by text), perimeter (length of edges), etc. Classification is carried out using the Support Vector Machine (SVM) as a classifier which transforms the nonlinear problem into linear using its kernel trick, logistic regression, KNN and at the end to enhance the classification rates we use Majority Voting. The experimental results obtained on a dataset of 282 writers with 2 samples per writer shows that the proposed method attains appealing performance on writer detection and text-independent environment.

     

Reputation based probabilistic resource allocation for avoiding free riding and formation of common interest groups in unstructured P2P networks

Free riding is a major problem in peer-to-peer networks. Reputation management systems are generally employed to overcome this problem. In this paper, a new reputation based scheme called probabilistic resource allocation is proposed. This strategy probabilistically decide whether to provide the resource to requesting peer or not. Aforesaid method gives selection preference to higher reputation peers and at the same time provides some finite probability of interaction between those peers who don’t have good reputation about each other. This avoids disconnection between the aforesaid peers. The proposed scheme also introduces a new mechanism for resource distribution which not only allocates resources based on peers’ reputation but simultaneously maximizes network utility also. Algorithm for formation of interest groups based upon both similarity of interests and reputation between peers is also presented.