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Chelmsford, MA, United States

Apollo Computer Inc., founded 1980 in Chelmsford, Massachusetts by William Poduska and others, developed and produced Apollo/Domain workstations in the 1980s. Along with Symbolics and Sun Microsystems, Apollo was one of the first vendors of graphical workstations in the 1980s. Apollo produced much of its own hardware and software.Apollo was acquired by Hewlett-Packard in 1989 for US$476 million, and gradually closed down over the period 1990-1997. Wikipedia.


Solley D.J.,Apollo Computer
Conference Proceedings - IEEE Applied Power Electronics Conference and Exposition - APEC | Year: 2015

D.C. multimeter, frequency sweeper and network analyzer. The circuit editor, which allows schematic entry, the above instruments and the analysis to be performed whether it be time domain, frequency domain or dc are all set up using a mouse and menu selections. The work bench offers a large model library, a parametric plotter and two statistical packages to boost engineering productivity. Some of its capabilities will be reviewed in the context of this paper. For the Spice connoisseur, the work bench will soon support Spice Plus, a C based version of Berkley 2G.6, which promises a 1.4X to 2.OX speed enhancement. To the first time user I would suggest he become familiar with Tnum, RELTOL, ABSTOL and VNTOL in the Analysis Options menu. Tnum defines the number of steps during the simulation. The default values for ABSTOL (absolute surrent error tolerance) and VNTOL (absolute voltage error tolerance) are 1.0E-12 and 1.0E-6 respectively and the author is not aware of too many power supply applications that require that kind of convergence accuracy. © 1986 IEEE.


Lakshmi Narayanan S.,Manonmaniam Sundaranar University | Vinukiran S.,Apollo Computer
Procedia Computer Science | Year: 2016

In this paper, we propose to transform the traditional cornea transplantation methods into an electronic exchange between the cornea donors and recipients in the cornea transplantation elective surgery. Preferential evaluations of recipient and donors (individuals / eye-bank) satisfactions are mathematically modeled, then the preference matrix is used as input for Gale Shapely matching algorithm. The results of m∗n match happens to be a very transparent approach in a bilateral e-cornea transplantation environment. These matched results are compared with the results obtained using Generalized Assignment problem which produces NP-hard approximated matches. It is found that the proposed method produces stable matching, which is preference based and strategy proof and it also reduces the need for number of iterations for matching. © 2016 The Authors.


Vinu Kiran S.,Apollo Computer | Prasanna Devi S.,Drmgr Educational And Research Institute University | Manivannan S.,Drmgr Educational And Research Institute University
Procedia Computer Science | Year: 2016

In this paper, we propose to transform the global matching mechanism in an electronic exchange between the producers and consumers in the SCM system for perishable commodities over large scale data sets. Matching of of consumers and producers satisfactions are mathematically modeled based on preferential evaluations based on the bidding request and the requirements data which is supplied as a matrix to Gale Shapely matching algorithm. The matching works over a very transparent approach in a e-trading environment over large scale data. Since, Bigdata is involved; the global SCM could be much clearer and easier for allocation of perishable commodities. These matching outcomes are compared with the matching and profit ranges obtained using simple English auction method which results Pareto-optimal matches. We are observing the proposed method produces stable matching, which is preference-strategy proof with incentive compatibility for both consumers and producers. Our design involves the preference revelation or elicitation problem and the preference-aggregation problem. The preference revelation problem involves eliciting truthful information from the agents about their types that are used for computation of Incentive compatible results. We are using Bayesian incentive compatible mechanism design in our match-making settings where the agents' preference types are multidimensional. This preserves profitability up to an additive loss that can be made arbitrarily small in polynomial time in the number of agents and the size of the agents' type spaces. © 2016 The Authors.


Bhanumathi R.,Apollo Computer | Suresh G.R.,Easwari Engineering College
2nd International Conference on Electronics and Communication Systems, ICECS 2015 | Year: 2015

Breast cancer has been most frequent form of common cancer in women. It is also the leading cause of mortality in women each year. Breast cancer is much less common in younger women and is most often diagnosed when women are over 60. Breast cancer is the second-most common and leading cause of cancer death among women. It has turn into a major health issue in the world over the past 50 years, and its occurrence has increased in recent years. One of the leading methods for diagnosing breast cancer is screening mammography. The appearance of micro-calcification in mammograms is an early sign of breast cancer. To overcome the issue automated micro-calcification detection techniques play a vital role in cancer diagnosis and treatment. This paper aims to develop an automatic system to classify the digital mammogram images into Benign or Malignant images. We have proposed Support vector machine (SVM) based classifier for to detect the microcalcification at each location in the mammogram images. The proposed method has been implemented in three stages (a) preprocessing (b) feature extraction (c) SVM classification. The proposed method has been evaluated using Mammogram Image Analysis Society (MIAS) database. Experimental results show that, when compared to several other methods SVM shows 94.94% micro calcification detection in mammograms. © 2015 IEEE.


Devi S.P.,Apollo Computer | Manivannan S.,Dr. M.G.R. Educational and Research Institute | Rao K.S.,Anna University
International Journal of Advanced Manufacturing Technology | Year: 2012

Abstract The primary aim of the paper is to compare the different nongradient methods of multiobjective optimization for optimizing the geometry parameters of a cylindrical fin heat sink. The methods studied for comparison are Taguchi-based grey relational analysis, ε (epsilon) constraint method and genetic algorithm. The various responses that have been studied are electromagnetic emitted radiations, thermal resistance and mass of the heat sink. Since the responses are obtained using complex simulation softwares (HFSS-Ansoft for emitted radiations and CFD-Flotherm for thermal resistance), there is no way of calculating the derivates of the objective functions. Hence, the Taguchi design of experiments design is used to derive the linear regression equations for the responses studied, which are then taken as the objective functions to be optimized. A new hybrid method known as Taguchi-based epsilon constraint method has been proposed in this paper for obtaining nondominated Pareto solution set. The results obtained using the proposed method show that the Pareto optimal set is competitive in terms of diversity of the solutions obtained. It is not likely that there exists a solution, which simultaneously minimizes all the objectives using any of the multiobjective techniques implemented. The value path analysis has been done to compare the trade-off among the design alternatives for the chosen multiple objective parameter optimization problem. ©Springer-Verlag London Limited 2012.

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