Prediction of Tool and Nozzle Flow Behavior in Ultrasonic Machining Process

The use of hard and brittle material has become increasingly more extensive in recent years. Therefore processing of these materials for the parts fabrication has become a challenging problem. However, it is time-consuming to machine the hard brittle materials with the traditional metal-cutting technique that uses abrasive wheels. In addition, the tool would suffer excessive wear as well. However, if ultrasonic energy is applied to the machining process and coupled with the use of hard abrasive grits, hard and brittle materials can be effectively machined. Ultrasonic machining process is mostly used for the brittle materials. The present research work has developed models using finite element approach to predict the mechanical stresses sand strains produced in the tool during ultrasonic machining process. Also the flow behavior of abrasive slurry coming out of the nozzle has been studied for simulation using ANSYS CFX module. The different abrasives of different grit sizes have been used for the experimentation work.

On the Wave Propagation in Layered Plates of General Anisotropic Media

Analysis for the propagation of elastic waves in arbitrary anisotropic plates is investigated, commencing with a formal analysis of waves in a layered plate of an arbitrary anisotropic media, the dispersion relations of elastic waves are obtained by invoking continuity at the interface and boundary of conditions on the surfaces of layered plate. The obtained solutions can be used for material systems of higher symmetry such as monoclinic, orthotropic, transversely isotropic, cubic, and isotropic as it is contained implicitly in the analysis. The cases of free layered plate and layered half space are considered separately. Some special cases have also been deduced and discussed. Finally numerical solution of the frequency equations for an aluminum epoxy is carried out, and the dispersion curves for the few lower modes are presented. The results obtained theoretically have been verified numerically and illustrated graphically.

Lung Nodule Detection in CT Scans

In this paper we describe a computer-aided diagnosis (CAD) system for automated detection of pulmonary nodules in computed-tomography (CT) images. After extracting the pulmonary parenchyma using a combination of image processing techniques, a region growing method is applied to detect nodules based on 3D geometric features. We applied the CAD system to CT scans collected in a screening program for lung cancer detection. Each scan consists of a sequence of about 300 slices stored in DICOM (Digital Imaging and Communications in Medicine) format. All malignant nodules were detected and a low false-positive detection rate was achieved.

On Methodologies for Analysing Sickness Absence Data: An Insight into a New Method

Sickness absence represents a major economic and social issue. Analysis of sick leave data is a recurrent challenge to analysts because of the complexity of the data structure which is often time dependent, highly skewed and clumped at zero. Ignoring these features to make statistical inference is likely to be inefficient and misguided. Traditional approaches do not address these problems. In this study, we discuss model methodologies in terms of statistical techniques for addressing the difficulties with sick leave data. We also introduce and demonstrate a new method by performing a longitudinal assessment of long-term absenteeism using a large registration dataset as a working example available from the Helsinki Health Study for municipal employees from Finland during the period of 1990-1999. We present a comparative study on model selection and a critical analysis of the temporal trends, the occurrence and degree of long-term sickness absences among municipal employees. The strengths of this working example include the large sample size over a long follow-up period providing strong evidence in supporting of the new model. Our main goal is to propose a way to select an appropriate model and to introduce a new methodology for analysing sickness absence data as well as to demonstrate model applicability to complicated longitudinal data.

pH-Responsiveness Properties of a Biodigradable Hydrogels Based on Carrageenan-g-poly(NaAA-co-NIPAM)

A novel thermo-sensitive superabsorbent hydrogel with salt- and pH-responsiveness properties was obtained by grafting of mixtures of acrylic acid (AA) and N-isopropylacrylamide (NIPAM) monomers onto kappa-carrageenan, kC, using ammonium persulfate (APS) as a free radical initiator in the presence of methylene bisacrylamide (MBA) as a crosslinker. Infrared spectroscopy was carried out to confirm the chemical structure of the hydrogel. Moreover, morphology of the samples was examined by scanning electron microscopy (SEM). The effect of MBA concentration and AA/NIPAM weight ratio on the water absorbency capacity has been investigated. The swelling variations of hydrogels were explained according to swelling theory based on the hydrogel chemical structure. The hydrogels exhibited salt-sensitivity and cation exchange properties. The temperature- and pH-reversibility properties of the hydrogels make the intelligent polymers as good candidates for considering as potential carriers for bioactive agents, e.g. drugs.

A Hybrid Approach for Quantification of Novelty in Rule Discovery

Rule Discovery is an important technique for mining knowledge from large databases. Use of objective measures for discovering interesting rules lead to another data mining problem, although of reduced complexity. Data mining researchers have studied subjective measures of interestingness to reduce the volume of discovered rules to ultimately improve the overall efficiency of KDD process. In this paper we study novelty of the discovered rules as a subjective measure of interestingness. We propose a hybrid approach that uses objective and subjective measures to quantify novelty of the discovered rules in terms of their deviations from the known rules. We analyze the types of deviation that can arise between two rules and categorize the discovered rules according to the user specified threshold. We implement the proposed framework and experiment with some public datasets. The experimental results are quite promising.

AI Applications to Metal Stamping Die Design– A Review

Metal stamping die design is a complex, experiencebased and time-consuming task. Various artificial intelligence (AI) techniques are being used by worldwide researchers for stamping die design to reduce complexity, dependence on human expertise and time taken in design process as well as to improve design efficiency. In this paper a comprehensive review of applications of AI techniques in manufacturability evaluation of sheet metal parts, die design and process planning of metal stamping die is presented. Further the salient features of major research work published in the area of metal stamping are presented in tabular form and scope of future research work is identified.

Reliability Analysis of Underground Pipelines Using Subset Simulation

An advanced Monte Carlo simulation method, called Subset Simulation (SS) for the time-dependent reliability prediction for underground pipelines has been presented in this paper. The SS can provide better resolution for low failure probability level with efficient investigating of rare failure events which are commonly encountered in pipeline engineering applications. In SS method, random samples leading to progressive failure are generated efficiently and used for computing probabilistic performance by statistical variables. SS gains its efficiency as small probability event as a product of a sequence of intermediate events with larger conditional probabilities. The efficiency of SS has been demonstrated by numerical studies and attention in this work is devoted to scrutinise the robustness of the SS application in pipe reliability assessment. It is hoped that the development work can promote the use of SS tools for uncertainty propagation in the decision-making process of underground pipelines network reliability prediction.

A Hybrid Approach for Color Image Quantization Using K-means and Firefly Algorithms

Color Image quantization (CQ) is an important problem in computer graphics, image and processing. The aim of quantization is to reduce colors in an image with minimum distortion. Clustering is a widely used technique for color quantization; all colors in an image are grouped to small clusters. In this paper, we proposed a new hybrid approach for color quantization using firefly algorithm (FA) and K-means algorithm. Firefly algorithm is a swarmbased algorithm that can be used for solving optimization problems. The proposed method can overcome the drawbacks of both algorithms such as the local optima converge problem in K-means and the early converge of firefly algorithm. Experiments on three commonly used images and the comparison results shows that the proposed algorithm surpasses both the base-line technique k-means clustering and original firefly algorithm.

Mode III Interlaminar Fracture in Woven Glass/Epoxy Composite Laminates

In the present study, fracture behavior of woven fabric-reinforced glass/epoxy composite laminates under mode III crack growth was experimentally investigated and numerically modeled. Two methods were used for the calculation of the strain energy release rate: the experimental compliance calibration (CC) method and the Virtual Crack Closure Technique (VCCT). To achieve this aim ECT (Edge Crack Torsion) was used to evaluate fracture toughness in mode III loading (out of plane-shear) at different crack lengths. Load–displacement and associated energy release rates were obtained for various case of interest. To calculate fracture toughness JIII, two criteria were considered including non-linearity and maximum points in load-displacement curve and it is observed that JIII increases with the crack length increase. Both the experimental compliance method and the virtual crack closure technique proved applicable for the interpretation of the fracture mechanics data of woven glass/epoxy laminates in mode III.

Study of the Effect of Project Management on Manufacturing and Production Projects

In this article the accumulated results out of the effects and length of the manufacture and production projects in the university and research standard have been settled with the usefulness definition of the process of project management for the accessibility to the proportional pattern in the “time and action" stages. Studies show that many problems confronted by the researchers in these projects are connected to the non-profiting of: 1) autonomous timing for gathering the educational theme, 2) autonomous timing for planning and pattern, presenting before the construction, and 3) autonomous timing for manufacture and sample presentation from the output. The result of this study indicates the division of every manufacture and production projects into three smaller autonomous projects from its kind, budget and autonomous expenditure, shape and order of the stages for the management of these kinds of projects. In this case study real result are compared with theoretical results.

A Comparison of Marginal and Joint Generalized Quasi-likelihood Estimating Equations Based On the Com-Poisson GLM: Application to Car Breakdowns Data

In this paper, we apply and compare two generalized estimating equation approaches to the analysis of car breakdowns data in Mauritius. Number of breakdowns experienced by a machinery is a highly under-dispersed count random variable and its value can be attributed to the factors related to the mechanical input and output of that machinery. Analyzing such under-dispersed count observation as a function of the explanatory factors has been a challenging problem. In this paper, we aim at estimating the effects of various factors on the number of breakdowns experienced by a passenger car based on a study performed in Mauritius over a year. We remark that the number of passenger car breakdowns is highly under-dispersed. These data are therefore modelled and analyzed using Com-Poisson regression model. We use the two types of quasi-likelihood estimation approaches to estimate the parameters of the model: marginal and joint generalized quasi-likelihood estimating equation approaches. Under-dispersion parameter is estimated to be around 2.14 justifying the appropriateness of Com-Poisson distribution in modelling underdispersed count responses recorded in this study.

Rigorous Modeling of Fixed-Bed Reactors Containing Finite Hollow Cylindrical Catalyst with Michaelis-Menten Type of Kinetics

A large number of chemical, bio-chemical and pollution-control processes use heterogeneous fixed-bed reactors. The use of finite hollow cylindrical catalyst pellets can enhance conversion levels in such reactors. The absence of the pellet core can significantly lower the diffusional resistance associated with the solid phase. This leads to a better utilization of the catalytic material, which is reflected in the higher values for the effectiveness factor, leading ultimately to an enhanced conversion level in the reactor. It is however important to develop a rigorous heterogeneous model for the reactor incorporating the two-dimensional feature of the solid phase owing to the presence of the finite hollow cylindrical catalyst pellet. Presently, heterogeneous models reported in the literature invariably employ one-dimension solid phase models meant for spherical catalyst pellets. The objective of the paper is to present a rigorous model of the fixed-bed reactors containing finite hollow cylindrical catalyst pellets. The reaction kinetics considered here is the widely used Michaelis–Menten kinetics for the liquid-phase bio-chemical reactions. The reaction parameters used here are for the enzymatic degradation of urea. Results indicate that increasing the height to diameter ratio helps to improve the conversion level. On the other hand, decreasing the thickness is apparently not as effective. This could however be explained in terms of the higher void fraction of the bed that causes a smaller amount of the solid phase to be packed in the fixed-bed bio-chemical reactor.

The use of Hormone Auxin in the Different Period Growth on Yield Components of Plant Vetch

The trial in the city, located 170 kilometers from the Iranian city of Ahvaz was Omidiyeh. The main factor in this project includes 4 levels in control (without hormones), use of hormones in the seed, vegetative and flowering stage respectively. And sub-plots included 3 varieties of vetch in three levels, with local names, was the jewel in the study of light and Auxin in the vegetative and reproductive different times in different varieties of vetch was investigated. This test has been taken in the plots in a randomized complete block with four replications. In order to study the effects of the hormone Auxin in the growth stages (seed, vegetative and flowering) to control (no hormone Auxin) on three local varieties of vetch, the essence of light and plant height, number of pods per plant, seed number The pods, seeds per plant, grain weight, grain yield, plant dry weight and protein content were measured. Among the vetch varieties for plant height, number of pods per plant, a seed per plant, grain weight, grain yield, and plant dry weight and protein levels of 1 percent of plant and seed number per pod per plant at 5% level of There was no significant difference. Interactions for grain yield per plant, grain yield and protein levels of 1 percent and the number of seeds per pod and seed weight are significant differences in levels 5 and plant height and plant dry weight of the interaction were INFLUENCE There was no significant difference in them.

Single-qubit Quantum Gates using Magneto-optic Kerr Effect

We propose the use of magneto-optic Kerr effect (MOKE) to realize single-qubit quantum gates. We consider longitudinal and polar MOKE in reflection geometry in which the magnetic field is parallel to both the plane of incidence and surface of the film. MOKE couples incident TE and TM polarized photons and the Hamiltonian that represents this interaction is isomorphic to that of a canonical two-level quantum system. By varying the phase and amplitude of the magnetic field, we can realize Hadamard, NOT, and arbitrary phase-shift single-qubit quantum gates. The principal advantage is operation with magnetically non-transparent materials.

Chemical Degradation of Dieldrin using Ferric Sulfide and Iron Powder

The chemical degradation of dieldrin in ferric sulfide and iron powder aqueous suspension was investigated in laboratory batch type experiments. To identify the reaction mechanism, reduced copper was used as reductant. More than 90% of dieldrin was degraded using both reaction systems after 29 days. Initial degradation rate of the pesticide using ferric sulfide was superior to that using iron powder. The reaction schemes were completely dissimilar even though the ferric ion plays an important role in both reaction systems. In the case of metallic iron powder, dieldrin undergoes partial dechlorination. This reaction proceeded by reductive hydrodechlorination with the generation of H+, which arise by oxidation of ferric iron. This reductive reaction was accelerated by reductant but mono-dechlorination intermediates were accumulated. On the other hand, oxidative degradation was observed in the reaction with ferric sulfide, and the stable chemical structure of dieldrin was decomposed into water-soluble intermediates. These reaction intermediates have no chemical structure of drin class. This dehalogenation reaction assumes to occur via the adsorbed hydroxyl radial generated on the surface of ferric sulfide.

Experiments and Modeling of Ion Exchange Resins for Nuclear Power Plants

Resins are used in nuclear power plants for water ultrapurification. Two approaches are considered in this work: column experiments and simulations. A software called OPTIPUR was developed, tested and used. The approach simulates the onedimensional reactive transport in porous medium with convectivedispersive transport between particles and diffusive transport within the boundary layer around the particles. The transfer limitation in the boundary layer is characterized by the mass transfer coefficient (MTC). The influences on MTC were measured experimentally. The variation of the inlet concentration does not influence the MTC; on the contrary of the Darcy velocity which influences. This is consistent with results obtained using the correlation of Dwivedi&Upadhyay. With the MTC, knowing the number of exchange site and the relative affinity, OPTIPUR can simulate the column outlet concentration versus time. Then, the duration of use of resins can be predicted in conditions of a binary exchange.

Multiple Moving Talker Tracking by Integration of Two Successive Algorithms

In this paper, an estimation accuracy of multiple moving talker tracking using a microphone array is improved. The tracking can be achieved by the adaptive method in which two algorithms are integrated, namely, the PAST (Projection Approximation Subspace Tracking) algorithm and the IPLS (Interior Point Least Square) algorithm. When either talker begins to speak again after a silent period, an appropriate feasible region for an evaluation function of the IPLS algorithm might not be set. Then, the tracking fails due to the incorrect updating. Therefore, if an increment of the number of active talkers is detected, the feasible region must be reset. Then, a low cost realization is required for the high speed tracking and a high accuracy realization is desired for the precise tracking. In this paper, the directions roughly estimated using the delayed-sum-array method are used for the resetting. Several results of experiments performed in an actual room environment show the effectiveness of the proposed method.

Modeling of Material Removal on Machining of Ti-6Al-4V through EDM using Copper Tungsten Electrode and Positive Polarity

This paper deals optimized model to investigate the effects of peak current, pulse on time and pulse off time in EDM performance on material removal rate of titanium alloy utilizing copper tungsten as electrode and positive polarity of the electrode. The experiments are carried out on Ti6Al4V. Experiments were conducted by varying the peak current, pulse on time and pulse off time. A mathematical model is developed to correlate the influences of these variables and material removal rate of workpiece. Design of experiments (DOE) method and response surface methodology (RSM) techniques are implemented. The validity test of the fit and adequacy of the proposed models has been carried out through analysis of variance (ANOVA). The obtained results evidence that as the material removal rate increases as peak current and pulse on time increases. The effect of pulse off time on MRR changes with peak ampere. The optimum machining conditions in favor of material removal rate are verified and compared. The optimum machining conditions in favor of material removal rate are estimated and verified with proposed optimized results. It is observed that the developed model is within the limits of the agreeable error (about 4%) when compared to experimental results. This result leads to desirable material removal rate and economical industrial machining to optimize the input parameters.