BATCH SEQUENCING

Consider the single machine scheduling problem where there are a number of part types to be processed. A part type is defined as follows: Two parts are of the same part type if the machine does not require a setup in between the processing of these parts. The problem investigated in this paper is to find a sequence of batches of parts (if there are any) where all the requirements for parts are met. A heuristic and an exact algorithm are developed, and computational analysis is performed to measure the performance of the heuristic. The time complexity function of the heuristic is O(n²), and the exact algorithm runs in polynomial time given a fixed upper bound on the number of setups.     

Robust estimation approach for blind denoising.

This work develops a new robust statistical framework for blind image denoising. Robust statistics addresses the problem of estimation when the idealized assumptions about a system are occasionally violated. The contaminating noise in an image is considered as a violation of the assumption of spatial coherence of the image intensities and is treated as an outlier random variable. A denoised image is estimated by fitting a spatially coherent stationary image model to the available noisy data using a robust estimator-based regression method within an optimal-size adaptive window. The robust formulation aims at eliminating the noise outliers while preserving the edge structures in the restored image. Several examples demonstrating the effectiveness of this robust denoising technique are reported and a comparison with other standard denoising filters is presented.     

Preparation and characterization of poly(methyl methacrylate)–lead silicate composites

Poly(methyl methacrylate)–lead silicate composites were prepared with different amounts of crystalline or amorphous PbO–SiO₂ binary composition (70 mole % PbO). The polymerization reaction was carried out in aqueous medium and in methanol–water mixture at 40°C using sodium bisulfite as initiator. The presence of lead silicate was found to increase the molecular weight of the poly(methyl methacrylate). The prepared composites were characterized by studying their shielding properties to γ radiation, mechanical hardness, dielectric constant, and thermal stability. It was found that lead silicate increases the absorbing power of the composites to γ radiation. This behavior was found to be dependent on the amount and the type of lead silicate (amorphous or crystalline). Gamma irradiation of the composites was found to cause chemical degradation of the poly(methyl methacrylate) leading to a decrease in mechanical hardness. Molecular weights of the poly(methyl methacrylate) for some of the composites were determined before and after irradiation viscosimetrically. Dielectric constants for some of the composites were determined at two different temperatures. The thermal stability of the composites was studied by means of an automatic thermogravimetric analyzer.     

Modification of polyolefins with silicone copolymers. II. Thermal,mechanical, and tribological behavior of PP and HDPE blended with silicone copolymers

Thermoplastic polyolefin (TPO) films with permanent, silicone‐rich, low‐friction, low‐abrasion surfaces were obtained by melt blending of high‐density polyethylene (HDPE) and polypropylene (PP) with polydimethylsiloxane (PDMS)‐containing block copolymers. Two different block copolymers, a siloxane–urea segmented copolymer and a polycaprolactone‐b‐PDMS triblock copolymer were used as modifiers at levels between 0.1 and 5.0% by weight. Blends were prepared in a twin‐screw extruder. Modified films displayed surfaces with very low friction coefficients and high abrasion resistance, which depended on the type and the level of additive incorporated into the system. Bulk properties of these modified systems, such as crystallization and melting behavior or tensile properties, were not affected. © 2002 Wiley Periodicals, Inc. J Appl Polym Sci 84: 535–540, 2002; DOI 10.1002/app.10279     

Tissue segmentation in ultrasound images by using genetic algorithms

This paper presents a genetic based incremental neural network (GINeN) for the segmentation of tissues in ultrasound images. Performances of the GINeN and the Kohonen network are investigated for tissue segmentation in ultrasound images. Feature extraction is carried out by using continuous wavelet transform. Pixel intensities at the same spatial location on 12 wavelet planes and on the original image are considered as features, leading to 13-dimensional feature vectors. The same training set is used for the training of the Kohonen network and the GINeN.

This paper proposes the use of wavelet transform and genetic based incremental neural network together in order to increase the segmentation performance. It is observed that genetic based incremental neural network gives satisfactory segmentation performance for ultrasound images.     

Medical image segmentation with transform and moment based features and incremental supervised neural network

In this study, a novel incremental supervised neural network (ISNN) is proposed for the segmentation of medical images. Performance of the ISNN is investigated for tissue segmentation in medical images obtained from various imaging modalities. Two feature extraction methods based on transform and moments are comparatively investigated to segment the tissues in medical images. Two-dimensional (2D) continuous wavelet transform (CWT) and the moments of the gray-level histogram (MGH) are computed in order to form the feature vectors of ultrasound (US) bladder and phantom images, X-ray computerized tomography (CT) and magnetic resonance (MR) head images. In the 2D-CWT method, feature vectors are formed by the intensity of one pixel of each wavelet-plane of different energy bands. The MGH represents the tissues within the sub-windows by using the spatial variation of image intensities. In this study, the ISNN and Grow and Learn (GAL) network are employed for the segmentation task. It is observed that the ISNN has significantly eliminated the disadvantages of the GAL network in the segmentation of the medical images.     

Radiation Synthesis and Magnetic Property Investigations of the Graft Copolymer Poly(Ethylene-g-Acrylic Acid)/Fe<Subscript>3</Subscript>O<Subscript>4</Subscript> Film

In this work, acrylic acid (AAc) monomer was grafted onto low-density polyethylene (LDPE) films by the direct method to obtain acid (LDPE-grafted poly(acrylic acid) (LDPE-g-PAAc)) graft copolymers. The presence of the grafted PAAc with COOH groups allows coupling with Fe^2+/3+ ions. The stabilization of Fe₃O₄ particles onto the graft copolymers was done by in situ reduction of LDPE-g-PAAc/Fe^2+/3+ with sodium borohydride (NaBH₄) in aqueous solution. The LDPE-g-PAAc graft copolymer and LDPE-g-PAAc/Fe₃O₄ composite films were characterized by scanning electron microscopy (SEM), X-ray diffraction (XRD), thermogravimetric analysis (TGA), Fourier transform infrared spectroscopy (FT-IR), differential scanning calorimetry (DSC), and electron spin resonance (ESR). The synthesized composites exhibit excellent magnetic properties. The results indicated that the magnetic oxide (Fe₃O₄) was embedded and homogenously dispersed into the surfaces of the graft copolymer films as indicated by SEM. The FT-IR analysis clearly suggests that an AAc monomer was effectively grafted onto LDPE. The XRD studies elucidate the change in the crystallinity of the graft copolymers.

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Graphical Abstract The procedures for magnetic film manufacture LDPE-g-PAAc/Fe₃O₄ using gamma irradiation technique