A fully automated hybrid methodology using Cuckoo‐based fuzzy clustering technique for magnetic resonance brain image segmentation

This article aims at developing an automated hybrid algorithm using Cuckoo Based Search (CBS) and interval type‐2 fuzzy based clustering, so as to exhibit efficient magnetic resonance (MR) brain image segmentation. An automatic MR brain image segmentation facilitates and enables a radiologist to have a brief review and easy analysis of complicated tumor regions of imprecise gray level regions with minimal user interface. The tumor region having severe intensity variations and suffering from poor boundaries are to be detected by the proposed hybrid technique that could ease the process of clinical diagnosis and this tends to be the core subject of this article. The ability of the proposed technique is compared using standard comparison parameters such as mean squared error, peak signal to noise ratio, computational time, Dice Overlap Index, and Jaccard T animoto C oefficient Index. The proposed CBS combined with interval type‐2 fuzzy based clustering produces a sensitivity of 0.7143 and specificity of 0.9375, which are far better than the conventional techniques such as kernel based, entropy based, graph‐cut based, and self‐organizing maps based clustering. Appreciable segmentation results of tumor region that enhances clinical diagnosis is made available through this article and two of the radiologists who have hands on experience in the field of radiology have extended their support in validating the efficiency of the proposed methodology and have given their consent in utilizing the proposed methodology in the processes of clinical oncology.     

Self-lubricating SU-8 Nanocomposites for Microelectromechanical Systems Applications

SU-8 is an industrially useful photoresist polymer for micro-fabrication because of its unique UV-sensitive curing property. It is also used as a structural material for micro-machines such as micro-electro mechanical systems (MEMS). However, it has poor tribological and mechanical properties which make SU-8 inferior to Si, the mainstay MEMS material today. In this paper, we report the fabrication of SU-8 nanocomposites which are self-lubricating and have better mechanical properties. The liquid lubricant i.e., perfluoropolyether (PFPE) and nanoparticles such as SiO₂, CNTs, and graphite were added into SU-8 for this purpose. These self-lubricating SU-8 + PFPE and SU-8 + PFPE + nanoparticle composites have shown a reduction in the initial coefficient of friction by ~6?C9 times and increased wear life by more than four orders of magnitude. The mechanical properties such as the elastic modulus and the hardness have increased by ~1.4 times. These SU-8 nanocomposites can be used as a self-lubricating structural material for MEMS applications requiring no external lubrication. As well, these nanocomposites can find applications in many tribological components of traditional machines.     

Study of performance and emission characteristics of IC engines by using diesel–water emulsion

Due to the shortage of petroleum products and its increasing cost, efforts are on to develop alternate fuels, especially diesel oil, for partial or full replacement. Also, internal combustion engines generate undesirable emissions during combustion process. The emissions exhausted in to the surroundings pollute the atmosphere and causes several problems. The emissions of concern are: unburnt hydrocarbons, oxides of carbon, and oxides of nitrogen (NO_X). Advanced diesel fuel formulations offer significant emission reductions to new and older in-use engines every time the fuel tank is filled. The addition of water to diesel fuel lowers particulate emissions by serving as diluents to the key combustion intermediates that lead to particulate formation. The incorporation of water also reduces NO_X emissions by lowering the peak combustion temperatures through high heat of vaporization. When using water blend diesel, the engine fuel system recognizes the liquid as diesel fuel because the water droplet is encapsulated within a diesel fuel. In this experiment, we have used single cylinder four-stroke engine and the water-blend diesel emulsion is used and the diesel emission test, emulsion emission test, and various gases has been analyzed; smoke meter test is also conducted for various rate of loads. The test results from the engine fuelled with water-blend diesel showed reduction in emissions as compared to that of engine fuelled with conventional diesel. The better emissions in the CI engine using water-blend diesel is due to the incorporation of water which reduces NO_X emissions by lowering the peak combustion temperatures. Water-blend fuel enhances fuel atomization by micro-explosion. The addition of water to diesel fuel lowers particulate emissions by serving as diluents to the key combustion intermediates that lead to particulate formation     

Different approaches for the loop layout problems: a review

In the manufacturing process, loop layout problems (LLPs) are preferred to configurations like single row layout, double row layout, cluster layout, and circular layout for their relative lower initial investment costs because they contain a minimal number of required material links to connect all workstations while providing a high degree of material handling flexibility. The performance of a system is based on the impact of the loop layout. Most of these LLPs are non-polynomial hard. Numerous research works related to loop layout have been published. The literature analysis given here is not restricted to specific considerations about loop layout design. This paper aims to deal with the current and future trends of research on LLPs based on previous research including formulations, solution methodologies. A trend toward bidirectional assumption, large-sized test problems, mixed integer programming, shortcuts instead of additional loop, loading and waiting time for shortcuts, integration of the supply chain management with the data envelopment analysis and also integrate exact, decomposition algorithm with metaheuristics, and developing loop layout using metaheuristics such as scatter search algorithm, improved tabu search, and artificial bees colony algorithm to loop layout is observed. Several research directions are pointed out and discussed.     

Experimental study of particle deposition characteristics of alumina using plasma spraying

Plasma spraying is one of the most versatile techniques used to form coatings for protection against oxidation, corrosion, and wear. The plasma spraying is ideally suited for refractory materials, but there are a number of variables that need to be controlled to obtain dense coatings. In spite of considerable progress made in the theoretical understanding of this complex process, there is a need for a simple method to evaluate the interaction between the plasma flame and powder particles that form the coatings. As reported in the literature, this involves metallographic observation of the powders collected from the plasma. In the present study, the structure and morphology of plasma-sprayed splats are experimentally investigated using different power levels and spray distances for alumina powder. The results show that the splashing occurs during splatting of a completely molten droplet. It is found that at higher power levels and shorter spray distances, spreading of molten droplets improves considerably.     

Ants colony algorithm approach for multi-objective optimisation of surface grinding operations

An ant colony based optimisation procedure has been developed to optimise grinding conditions, viz. wheel speed, workpiece speed, depth of dressing and lead of dressing, using a multi-objective function model with a weighted approach for the surface grinding process. The procedure evaluates the production cost and production rate for the optimum grinding condition, subjected to constraints such as thermal damage, wheel wear parameters, machine tool stiffness and surface finish. The results are compared with Genetic Algorithm (GA) and Quadratic Programming (QP) techniques.Nomenclature a _p down feed of grinding (mm/pass) - a _w total thickness of cut (mm) - A _o initial wear flat-area percentage (%) - b _e empty width of grinding (mm) - b _s width of wheel (mm) - b _w width of workpiece (mm) - B _k positive definite approximation of the Hessian - doc depth of dressing (mm) - c _d cost of dressing ($) - c _s cost of wheel per mm³ ($/mm³) - CT total production cost ($/pc) - CT ^* expected production cost limit ($/pc) - d _g grind size (mm) - D _e diameter of wheel (mm) - f _b cross feed rate (mm/pass) - G grinding ratio - k _a constant dependent on coolant and wheel grind type - k _u wear constant (mm^-1) - k _c cutting stiffness (N/mm) - k _m static machine stiffness (N/mm) - k _s wheel wear stiffness (N/mm) - L lead of dressing (mm/rev) - L _e empty length of grinding (mm) - L _w length of workpiece (mm) - M _c cost per hour labour and administration ($/h) - N _d total number of pieces to be grouped during the life of dressing (pc) - N _t batch size of workpieces (pc) - N _td total number of workpieces to be grouped during the life of dressing (pc) - P number of workpieces loaded on the table (pc) - R _a surface roughness (µm) - R _a* surface finish limit during rough grinding (µm) - R _c workpiece hardness (Rockwell hardness number) - R _em dynamic machine characteristics - S _d distance of wheel idling (mm) - S _p number of spark out grinding (pass) - t _sh time of adjusting machine tool (min) - t _i time of loading and unloading workpiece (min) - T _ave average chip thickness during grinding (µm) - U specific grinding energy (J/mm) - U ^* critical specific grinding energy (J/mm³) - V _r speed of wheel idling (mm/min) - V _s wheel speed (m/min) - V _w workpiece speed (m/min) - VOL wheel bond percentage (%) - WRP workpiece removal parameter (mm³/min-N) - WRP ^* workpiece removal parameter limit (mm³/min-N) - WWP wheel wear parameter (mm³/min-N) - W _i weighting factor, 0W _i1 (W ₁+W ₂+W ₃=1)     

Synthesis and characterization of Y3Al5O12 and ZrO2-Y2O3 thermal barrier coatings by combustion spray pyrolysis

Y₃Al₅O₁₂ and ZrO₂-Y₂O₃ (8 mol% YSZ) coatings for potential application as thermal barrier coatings were prepared by combustion spray pyrolysis. Thermal cycling of as deposited coatings on stainless steel and FeCrAlY bond coat substrates was carried out at 1000 °C and 1200 °C to determine the thermal fatigue response. Structural and morphological studies on Y₃Al₅O₁₂ and 8 mol% YSZ coatings before and after thermal cycling have been carried out. It has been noted that the coatings on FeCrAlY substrates remain intact after 50 cycles between room temperature and 1200 °C, whereas the coatings on stainless steel show some minor damage such as peeling off near the periphery after 50 cycles at 1000 °C. Thermal diffusivity values of Y₃Al₅O₁₂ and 8 mol% YSZ films were measured by using photo thermal deflection spectroscopy and the values are lower than those of coatings produced by conventional techniques such as EBPVD and APS.     

The Role of Functional End Groups of Perfluoropolyether (Z-dol and Z-03) Lubricants in Augmenting the Tribology of SU-8 Composites

In an earlier work, we demonstrated the development of SU-8 composites using perfluoropolyether (PFPE) as lubricant filler which reduced friction coefficient by ~7 times and enhanced wear life of SU-8 by more than four orders of magnitude. In this work, we have investigated the role of chemical bonding between SU-8 and PFPE molecules using two types of PFPE lubricants (i.e., Fomblin^® Z-dol and Z-03) in improving the tribological properties of the composite. Z-dol has polar (–OH) end groups whereas Z-03 has non-polar (CF₃) end groups. SU-8 with Z-dol (SU-8 + Z-dol) films yielded ~8 times greater wear life than SU-8 with Z-03 (SU-8 + Z-03) films and more by four orders of magnitude than pure SU-8. The nature of the films was analyzed in detail by chemical and physical characterization techniques like X-ray photoelectron spectroscopy, water contact angle and thermo-gravimetric analysis. The results validated the role of polar end functional group of Z-dol in covalent binding with SU-8 upon UV plasma treatment that resulted in improved tribological properties.     

Molecular interactions of graphene with HIV-Vpr,Nef and Gag proteins: A new approach for treating HIV infections

Graphene draws considerable attention among biomedical researchers because of its unique physical, chemical and biological properties. The wide applications of graphene in the biomedical arena such as diagnostics, drug immobilization and drug delivery were well documented in the literature. However the therapeutic potential of the graphene towards retroviruses and the interactions of the graphene with receptors/proteins are still unexplored. Herein we report the antagonistic molecular interactions of graphene with the three key target proteins of HIV infections namely HIVVpr, Nef and Gag proteins. The docking investigations were performed to find the binding energy of the graphene ligands to the key target proteins of HIV. The high binding affinity of the graphene to these proteins indicates the antagonistic molecular interaction of graphene to the disease targets. The therapeutic potential of graphene was also studied by changing the size and the number of layers of the graphene. The experimental results confirm the good therapeutic potential of the graphene to combat HIV mediated retroviral infections.     

Evolutionary optimal trajectory planning for industrial robot with payload constraints

This paper presents a new general methodology based on the evolutionary algorithms—elitist non-dominated sorting genetic algorithm (NSGA-II) and differential evolution (DE)—for optimal trajectory planning of an industrial robot manipulator (PUMA560) by considering payload constraints. The aim is to minimize a multicriterion cost function with actuator constraints, joint limits, and payload constraints by considering dynamic equations of motion. Trajectories are defined by B-spline functions. This is a nonlinear constrained optimisation problem with five objective functions, 32 constraints, and 252 variables. The multicriterion cost function is a weighted balance of transfer time, total energy involved in the motion, singularity avoidance, joint jerks, and joint accelerations. A numerical example is presented for showing the efficiency of the proposed procedure. Also, the results obtained from NSGA-II and DE techniques are compared and analysed. A comprehensive user-friendly general-purpose software package has been developed using VC++ to obtain optimal solutions using the proposed DE algorithm.