Quality and Defect Prediction in Plastic Injection Molding using Machine Learning Algorithms based Gating Systems and Its Mathematical Models

To achieve high quality products from Plastic Injection Molding (PIM) process it is very essential to identify the defective operations in automatic manner which is most challenging task. This paper proposes a Machine Learning (ML) approach to detect the complex faults occurrence during the PIM process. During initial sampling process of molding to achieve high quality and low time consumption it is essential to concentrate on the suitable determination of parameter values by considering the properties of injection molding process. For that purpose, a novel machine learning algorithms based gating system is introduced in PIM (MLGS-PIM). Technical evaluation can be done using simulation which combines the CATIA and MATLAB. Therefore in MLGS-PIM, a holistic approach is introduced to improve and predict the process quality of the parameters which is based on machine learning approaches. The considered machine learning approaches for this process are Artificial Neural Network (ANN) and Support Vector Machine (SVM). This two learning models are combined to achieve high quality under various conditions. Such novel ML based technique helps to increase the quality characteristics of the injection molding process and it is predicted with various parameter values where the simulation data and measurements are handled in an intelligent manner. The materials which are considered in the PIM process are thermoplastic polystyrene, thermoplastic acrylonitrile butadiene styrene and thermoplastic polyvinyl chloride where three types are gating systems are applied with it and consists of 3, 4 and 5 gates and as well the parameters which are measured for the output analysis are sum rate, bit error rate and convergence plot. The results show that the performance of the proposed MLGS-PIM approach significantly increases the performance when compared with the earlier approaches such as AntLion Optimization and PSO-MSQPA

Fishery potential along the Indian coastal waters between Porbandar and Ratnagiri

As part of the ongoing marine pollution monitoring programme the coastal stretch between Porbandar and Ratnagiri was considered to assess the fishery potential. Regular experimental trawling was done off Porbandar, Veraval, Diu, Hazira, Daman, Bassein, Bombay, Murud and Ratnagiri at a depth range of 5-25 m during 1988 to 1992. The catch rate varied from 1.2 to 225 kg/h (av.20.3 kg/h). Zonewise maximum catch (av.56.8 kg/h) was observed off Ratnagiri followed by off Porbandar (av.30.1 kg/h), off Bombay (av.23.9 kg/h) and off Murud (av.19.8 kg/h). The area between Hazira and Daman was poor in fish catch. In general, the catch rate showed a fluctuating trend during the period of observation. Among the hundred species identified from the collections the most common species were Coilia dussumieri, Johnius glaucus, Scoliodon laticaudus, Lepturacanthus savala, Harpadon nehereus, Sardinella longiceps, Pampus sp. and Congresox sp. The community structure and species assemblage at different zones are discussed in detail

A case study on the impact of industrial effluent disposal on the fishery of Amba River estuary, Maharashtra

The impact of waste discharge on fishery resources is a matter of great concern. The accepted norm in all environmental impact assessment studies is to avoid areas of high fishery potential while locating a marine outfall. Contemplating on this aspect a case study was conducted in the Amba River estuary before and after the establishment of a petrochemical complex at Nagothane. The treated wastewater from this complex is released through a subsurface outfall after adopting effective control measures for marine disposal of waste. Experimental trawling was done at five locations covering a distance of 30 km during 1990 to 1991. The catch rate within the estuary varied from 0.6 to 255 kg/h (av 24 kg/h). The trend indicated considerable decrease in fishery potential from the mouth of the estuary (av 64 kg/h) to the upstream location (av 11 kg/h). A total of 49 species of fishes, 16 species of prawns, 7 species of crabs and 1 species of lobster were identified from the collections. Number of species gradually increased from the interior segment at Dharamtar (8) to the outer area near Revas (18). A comparison of the quantitative and qualitative nature of the post outfall and pre outfall data revealed only marginal difference. The study indicates that if necessary precautions are taken to render the waste harmless the marine ecology will hardly be affected

Scaling of Level Statistics at the Disorder-Induced Metal-Insulator Transition

The distribution of energy level separations for lattices of sizes up to 28$\times$28$\times$28 sites is numerically calculated for the Anderson model. The results show one-parameter scaling. The size-independent universality of the critical level spacing distribution allows to detect with high precision the critical disorder $W_{c}=16.35$. The scaling properties yield the critical exponent, $\nu =1.45 \pm 0.08$, and the disorder dependence of the correlation length.Comment: 11 pages (RevTex), 3 figures included (tar-compressed and uuencoded using UUFILES), to appear in Phys.Rev. B 51 (Rapid Commun.

A study on innovativeness and regulating conflicts between the fishers and farmers in the Balua wetland

Wetlands store ground and surface water even when the rainfall is erratic. However, the rising demand for water and land to sustain the ever increasing population has manifested in many kinds of conflicts in wetlands. In the study area, Balua Chaur (wetland) in Bihar state of India, 16 conflicts emerged when the flooded lands offarmers was accessed by the fishers to fish. Such conflicts had further marginalized the already indigent fishers. Factor analysis, to reduce the socioeconomic and psychological variables of the fishers that were associated with innovativeness and further analysis of ANOVA and regression was used. In case of fishers, two major groups of interrelated variables that accounted for 60.6 % of the total variance were identified through this method. Factor 1 accounted for 34.8 % of the total variance that included innovativeness, income, education, mass media exposure, extension contact, livestock ownership, land ownership, mobile use collaborating and competing style of conflict management and named as innovative factors. The ANOVA table and stepwise multiple regression model exhibited that the nuclear family type and livestock have significant impact on the innovativeness of fishers with R2 value 0.255. In this paper, peace and prosperity model based upon the analysis of primary information collected from the fishers, farmers and key informants is proposed to foster innovativeness to enhance the productivity of wetland and resolve conflict to mobilize the resources in efficient and judicial manner

Geometric Phase: a Diagnostic Tool for Entanglement

Using a kinematic approach we show that the non-adiabatic, non-cyclic, geometric phase corresponding to the radiation emitted by a three level cascade system provides a sensitive diagnostic tool for determining the entanglement properties of the two modes of radiation. The nonunitary, noncyclic path in the state space may be realized through the same control parameters which control the purity/mixedness and entanglement. We show analytically that the geometric phase is related to concurrence in certain region of the parameter space. We further show that the rate of change of the geometric phase reveals its resilience to fluctuations only for pure Bell type states. Lastly, the derivative of the geometric phase carries information on both purity/mixedness and entanglement/separability.Comment: 13 pages 6 figure

Exact Minimum Eigenvalue Distribution of an Entangled Random Pure State

A recent conjecture regarding the average of the minimum eigenvalue of the reduced density matrix of a random complex state is proved. In fact, the full distribution of the minimum eigenvalue is derived exactly for both the cases of a random real and a random complex state. Our results are relevant to the entanglement properties of eigenvectors of the orthogonal and unitary ensembles of random matrix theory and quantum chaotic systems. They also provide a rare exactly solvable case for the distribution of the minimum of a set of N {\em strongly correlated} random variables for all values of N (and not just for large N).Comment: 13 pages, 2 figures included; typos corrected; to appear in J. Stat. Phy

Steady State Behavior of Mechanically Perturbed Spin Glasses and Ferromagnets

A zero temperature dynamics of Ising spin glasses and ferromagnets on random graphs of finite connectivity is considered, like granular media these systems have an extensive entropy of metastable states. We consider the problem of what energy a randomly prepared spin system falls to before becoming stuck in a metastable state. We then introduce a tapping mechanism, analogous to that of real experiments on granular media, this tapping, corresponding to flipping simultaneously any spin with probability $p$, leads to stationary regime with a steady state energy $E(p)$. We explicitly solve this problem for the one dimensional ferromagnet and $\pm J$ spin glass and carry out extensive numerical simulations for spin systems of higher connectivity. The link with the density of metastable states at fixed energy and the idea of Edwards that one may construct a thermodynamics with a flat measure over metastable states is discussed. In addition our simulations on the ferromagnetic systems reveal a novel first order transition, whereas the usual thermodynamic transition on these graphs is second order.Comment: 11 pages, 7 figure

Spectra of "Real-World" Graphs: Beyond the Semi-Circle Law

Many natural and social systems develop complex networks, that are usually modelled as random graphs. The eigenvalue spectrum of these graphs provides information about their structural properties. While the semi-circle law is known to describe the spectral density of uncorrelated random graphs, much less is known about the eigenvalues of real-world graphs, describing such complex systems as the Internet, metabolic pathways, networks of power stations, scientific collaborations or movie actors, which are inherently correlated and usually very sparse. An important limitation in addressing the spectra of these systems is that the numerical determination of the spectra for systems with more than a few thousand nodes is prohibitively time and memory consuming. Making use of recent advances in algorithms for spectral characterization, here we develop new methods to determine the eigenvalues of networks comparable in size to real systems, obtaining several surprising results on the spectra of adjacency matrices corresponding to models of real-world graphs. We find that when the number of links grows as the number of nodes, the spectral density of uncorrelated random graphs does not converge to the semi-circle law. Furthermore, the spectral densities of real-world graphs have specific features depending on the details of the corresponding models. In particular, scale-free graphs develop a triangle-like spectral density with a power law tail, while small-world graphs have a complex spectral density function consisting of several sharp peaks. These and further results indicate that the spectra of correlated graphs represent a practical tool for graph classification and can provide useful insight into the relevant structural properties of real networks.Comment: 14 pages, 9 figures (corrected typos, added references) accepted for Phys. Rev.

Energy-level statistics at the metal-insulator transition in anisotropic systems

We study the three-dimensional Anderson model of localization with anisotropic hopping, i.e. weakly coupled chains and weakly coupled planes. In our extensive numerical study we identify and characterize the metal-insulator transition using energy-level statistics. The values of the critical disorder $W_c$ are consistent with results of previous studies, including the transfer-matrix method and multifractal analysis of the wave functions. $W_c$ decreases from its isotropic value with a power law as a function of anisotropy. Using high accuracy data for large system sizes we estimate the critical exponent $\nu=1.45\pm0.2$. This is in agreement with its value in the isotropic case and in other models of the orthogonal universality class. The critical level statistics which is independent of the system size at the transition changes from its isotropic form towards the Poisson statistics with increasing anisotropy.Comment: 22 pages, including 8 figures, revtex few typos corrected, added journal referenc