987 resultados para design pattern
Resumo:
Data mining is one of the hottest research areas nowadays as it has got wide variety of applications in common man’s life to make the world a better place to live. It is all about finding interesting hidden patterns in a huge history data base. As an example, from a sales data base, one can find an interesting pattern like “people who buy magazines tend to buy news papers also” using data mining. Now in the sales point of view the advantage is that one can place these things together in the shop to increase sales. In this research work, data mining is effectively applied to a domain called placement chance prediction, since taking wise career decision is so crucial for anybody for sure. In India technical manpower analysis is carried out by an organization named National Technical Manpower Information System (NTMIS), established in 1983-84 by India's Ministry of Education & Culture. The NTMIS comprises of a lead centre in the IAMR, New Delhi, and 21 nodal centres located at different parts of the country. The Kerala State Nodal Centre is located at Cochin University of Science and Technology. In Nodal Centre, they collect placement information by sending postal questionnaire to passed out students on a regular basis. From this raw data available in the nodal centre, a history data base was prepared. Each record in this data base includes entrance rank ranges, reservation, Sector, Sex, and a particular engineering. From each such combination of attributes from the history data base of student records, corresponding placement chances is computed and stored in the history data base. From this data, various popular data mining models are built and tested. These models can be used to predict the most suitable branch for a particular new student with one of the above combination of criteria. Also a detailed performance comparison of the various data mining models is done.This research work proposes to use a combination of data mining models namely a hybrid stacking ensemble for better predictions. A strategy to predict the overall absorption rate for various branches as well as the time it takes for all the students of a particular branch to get placed etc are also proposed. Finally, this research work puts forward a new data mining algorithm namely C 4.5 * stat for numeric data sets which has been proved to have competent accuracy over standard benchmarking data sets called UCI data sets. It also proposes an optimization strategy called parameter tuning to improve the standard C 4.5 algorithm. As a summary this research work passes through all four dimensions for a typical data mining research work, namely application to a domain, development of classifier models, optimization and ensemble methods.
Resumo:
With the recent progress and rapid increase in the field of communication, the designs of antennas for small mobile terminals with enhanced radiation characteristics are acquiring great importance. Compactness, efficiency, high data rate capacity etc. are the major criteria for the new generation antennas. The challenging task of the microwave scientists and engineers is to design a compact printed radiating structure having broadband behavior along with good efficiency and enhanced gain. Printed antenna technology has received popularity among antenna scientists after the introduction of planar transmission lines in mid-seventies. When we view the antenna through a transmission line concept, the mechanism behind any electromagnetic radiator is quite simple and interesting. Any electromagnetic system with a discontinuity is radiating electromagnetic energy. The size, shape and orientation of the discontinuities control the radiation characteristics of the system such as radiation pattern, gain, polarization etc. It can be either resonant or non-resonant. This thesis deals with antennas that are developed from a class of transmission lines known as coplanar strip-CPS, a planar analogy of parallel pair transmission line. The specialty of CPS is its symmetric structure compared to other transmission lines, which makes the antenna structures developed from CPS quite simple for design and fabrication. The structural modifications on either metallic strip of CPS results in different antennas. The first part of the thesis discusses a single band and dual band design derived from open ended slot lines which are very much suitable for 2.4 and 5.2 GHz WLAN applications. The second section of the study is vectored into the development of enhanced gain dipoles. A single band dipole and a wide band enhanced gain dipole suitable for 5.2/5.8 GHZ band and imaging applications are developed and discussed. Last part of the thesis discusses the development of directional UWBs. Three different types of ultra-compact UWBs are developed and almost all the frequency domain and time domain analysis of the structures are discussed.
Resumo:
A marine isolate of jáÅêçÅçÅÅìë MCCB 104 has been identified as an aquaculture probiotic antagonistic to sáÄêáç. In the present study different carbon and nitrogen sources and growth factors in a mineral base medium were optimized for enhanced biomass production and antagonistic activity against the target pathogen, sáÄêáç=Ü~êîÉóá, following response surface methodology (RSM). Accordingly the minimum and maximum limits of the selected variables were determined and a set of fifty experiments programmed employing central composite design (CCD) of RSM for the final optimization. The response surface plots of biomass showed similar pattern with that of antagonistic activity, which indicated a strong correlation between the biomass and antagonism. The optimum concentration of the carbon sources, nitrogen sources, and growth factors for both biomass and antagonistic activity were glucose (17.4 g/L), lactose (17 g/L), sodium chloride (16.9 g/L), ammonium chloride (3.3 g/L), and mineral salts solution (18.3 mL/L). © KSBB
Resumo:
Formalizing algorithm derivations is a necessary prerequisite for developing automated algorithm design systems. This report describes a derivation of an algorithm for incrementally matching conjunctive patterns against a growing database. This algorithm, which is modeled on the Rete matcher used in the OPS5 production system, forms a basis for efficiently implementing a rule system. The highlights of this derivation are: (1) a formal specification for the rule system matching problem, (2) derivation of an algorithm for this task using a lattice-theoretic model of conjunctive and disjunctive variable substitutions, and (3) optimization of this algorithm, using finite differencing, for incrementally processing new data.
Resumo:
In all biological processes, protein molecules and other small molecules interact to function and form transient macromolecular complexes. This interaction of two or more molecules can be described by a docking event. Docking is an important phase for structure-based drug design strategies, as it can be used as a method to simulate protein-ligand interactions. Various docking programs exist that allow automated docking, but most of them have limited visualization and user interaction. It would be advantageous if scientists could visualize the molecules participating in the docking process, manipulate their structures and manually dock them before submitting the new conformations to an automated docking process in an immersive environment, which can help stimulate the design/docking process. This also could greatly reduce docking time and resources. To achieve this, we propose a new virtual modelling/docking program, whereby the advantages of virtual modelling programs and the efficiency of the algorithms in existing docking programs will be merged.
Resumo:
Context: Evidence is limited on the effects of different patterns of use of postmenopausal hormone therapy on fracture incidence and particularly on the effects of ceasing use. Objective: To investigate the effect of different patterns of hormone therapy use on fracture incidence. Design, Setting, and Participants: Prospective study of 138737 postmenopausal women aged 50 to 69 years recruited from the UK general population in 19961998 (the Million Women Study) and followed up for 1.9 to 3.9 years (average, 2.8 years) for fracture incidence. Main Outcome Measure: Adjusted relative risk (RR) for incident fracture (except fracture of the fingers, toes, and ribs) in hormone therapy users compared with never users at baseline. Results: A total of 5197 women (3.7%) reported 1 or more fractures, 79% resulting from falls. Current users of hormone therapy at baseline had a significantly reduced incidence of fracture (RR, 0.62; 95% confidence interval [CI], 0.58-0.66; P<.001). This protection was evident soon after hormone therapy began, and the RR decreased with increasing duration of use (P=.001). Among current users at baseline the RR of fracture did not vary significantly according to whether estrogen-only, estrogen-progestin, or other types of hormones were used (RR [95% CI], 0.64 [0.58-0.71], 0.58 [0.53-0.64], and 0.67 [0.56-0.80], respectively; P=19), nor did it vary significantly according to estrogen dose or estrogen or progestin constituents. The RR associated with current use of hormone therapy did not vary significantly according to 11 personal characteristics of study participants, including their age at menopause, body mass index, and physical activity. Past users of hormone therapy at baseline experienced no significant protection against fractures (RR, 1.07; 95% CI, 0.99-1.15); incidence rates returned to those of never-users within about a year of ceasing use. Conclusions: All types of hormone therapy studied confer substantial protection against fracture while they are used. This protection appears rapidly after use commences and wears off rapidly after use ceases. The older women are, the greater is their absolute reduction in fracture incidence while using hormone therapy.
Resumo:
An approach to the automatic generation of efficient Field Programmable Gate Arrays (FPGAs) circuits for the Regular Expression-based (RegEx) Pattern Matching problems is presented. Using a novel design strategy, as proposed, circuits that are highly area-and-time-efficient can be automatically generated for arbitrary sets of regular expressions. This makes the technique suitable for applications that must handle very large sets of patterns at high speed, such as in the network security and intrusion detection application domains. We have combined several existing techniques to optimise our solution for such domains and proposed the way the whole process of dynamic generation of FPGAs for RegEX pattern matching could be automated efficiently.
Resumo:
Purpose: The purpose of this paper is to address a classic problem – pattern formation identified by researchers in the area of swarm robotic systems – and is also motivated by the need for mathematical foundations in swarm systems. Design/methodology/approach: The work is separated out as inspirations, applications, definitions, challenges and classifications of pattern formation in swarm systems based on recent literature. Further, the work proposes a mathematical model for swarm pattern formation and transformation. Findings: A swarm pattern formation model based on mathematical foundations and macroscopic primitives is proposed. A formal definition for swarm pattern transformation and four special cases of transformation are introduced. Two general methods for transforming patterns are investigated and a comparison of the two methods is presented. The validity of the proposed models, and the feasibility of the methods investigated are confirmed on the Traer Physics and Processing environment. Originality/value: This paper helps in understanding the limitations of existing research in pattern formation and the lack of mathematical foundations for swarm systems. The mathematical model and transformation methods introduce two key concepts, namely macroscopic primitives and a mathematical model. The exercise of implementing the proposed models on physics simulator is novel.
Resumo:
Cellular neural networks (CNNs) have locally connected neurons. This characteristic makes CNNs adequate for hardware implementation and, consequently, for their employment on a variety of applications as real-time image processing and construction of efficient associative memories. Adjustments of CNN parameters is a complex problem involved in the configuration of CNN for associative memories. This paper reviews methods of associative memory design based on CNNs, and provides comparative performance analysis of these approaches.
From Rational Design of Drug Crystals to Understanding of Nucleic Acid Structures: Lamivudine Duplex
Resumo:
A DNA-like duplex of nucleosides is probable to exist even without the 5`-phosphate groups needed to assemble the chain backbone. However, double-stranded helical structures of nucleosides are unknown. Here, we report a duplex of nucleoside analogs that is spontaneously assembled due to stacking of the neutral and protonated molecules of lamivudine, a nucleoside reverse transcriptase inhibitor (NTRI) widely used in anti-HIV drug combinatory medication. The left-handed lamivudine duplex has features similar to those of i-motif DNA, as the face-to-face base stacking and the helix rise per base pair. Furthermore, the protonation pattern on alternate bases expected for it DNA-like duplex stabilized by pairing of neutral and protonated cytosine fragments was observed for the first time in the lamivudine double-stranded helix. This structure demonstrates that hydrogen bonds can substitute for covalent phosphodiester linkage in the stabilization of the duplex backbone. This interesting example of spontaneous molecular self-organization indicates that the 5`-phosphate group could not be a requirement for duplex assembly.
Resumo:
The design of translation invariant and locally defined binary image operators over large windows is made difficult by decreased statistical precision and increased training time. We present a complete framework for the application of stacked design, a recently proposed technique to create two-stage operators that circumvents that difficulty. We propose a novel algorithm, based on Information Theory, to find groups of pixels that should be used together to predict the Output Value. We employ this algorithm to automate the process of creating a set of first-level operators that are later combined in a global operator. We also propose a principled way to guide this combination, by using feature selection and model comparison. Experimental results Show that the proposed framework leads to better results than single stage design. (C) 2009 Elsevier B.V. All rights reserved.
Resumo:
Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
Resumo:
A body of research has developed within the context of nonlinear signal and image processing that deals with the automatic, statistical design of digital window-based filters. Based on pairs of ideal and observed signals, a filter is designed in an effort to minimize the error between the ideal and filtered signals. The goodness of an optimal filter depends on the relation between the ideal and observed signals, but the goodness of a designed filter also depends on the amount of sample data from which it is designed. In order to lessen the design cost, a filter is often chosen from a given class of filters, thereby constraining the optimization and increasing the error of the optimal filter. To a great extent, the problem of filter design concerns striking the correct balance between the degree of constraint and the design cost. From a different perspective and in a different context, the problem of constraint versus sample size has been a major focus of study within the theory of pattern recognition. This paper discusses the design problem for nonlinear signal processing, shows how the issue naturally transitions into pattern recognition, and then provides a review of salient related pattern-recognition theory. In particular, it discusses classification rules, constrained classification, the Vapnik-Chervonenkis theory, and implications of that theory for morphological classifiers and neural networks. The paper closes by discussing some design approaches developed for nonlinear signal processing, and how the nature of these naturally lead to a decomposition of the error of a designed filter into a sum of the following components: the Bayes error of the unconstrained optimal filter, the cost of constraint, the cost of reducing complexity by compressing the original signal distribution, the design cost, and the contribution of prior knowledge to a decrease in the error. The main purpose of the paper is to present fundamental principles of pattern recognition theory within the framework of active research in nonlinear signal processing.
Resumo:
The design of the present study enabled the authors to distinguish between the possible effects of movement displacement and trajectory length on the pattern of final positions of planar reaching movements. With their eyes closed, 9 subjects performed series of fast and accurate movements from different initial positions to the same target. For some series, the movements were unconstrained and were therefore performed along an approximately straight vertical line. For other series, an obstacle was positioned so that trajectory length was increased because of an increase in movement curvature. Ellipses of variability obtained by means of principal component analysis applied to the scatter of movement final positions enabled the authors to assess the pattern of movement variable errors. The results showed that the orientation of the ellipses was not affected by movement displacement or by trajectory length, whereas variable errors increased with move ment displacement. An increase in trajectory length as a consequence of increased curvature caused no change in variable error. From the perspective of current motor control theory, that finding was quite unexpected. Further studies are required so that one can distinguish among the possible effects of various kinematics, kinetics, and other variables that could affect the pattern of variable errors of reaching movements.
Resumo:
Objective. The aim of this study was to perform quantitative and qualitative analyses of the initial repair pattern of an autogenous bone block graft when covered or not with e-PTFE membranes. Study design. Sixty male Wistar rats received a bone graft plus an e-PTFE membrane (MB) or just the graft (B). A block graft was harvested from the animal's calvarium and was laid and stabilized on the external cortical area near the angle of the mandible. Descriptive histology and histomorphometric analyses were carried out and the data were analyzed statistically by ANOVA and the Tukey test, with the level of significance set at 5%. Results. The results for group B showed that there was bone loss during the healing period (B0 = 1.38, B45 = 1.05, F = 7.91 > F C = 3.02), that is, the initial volume of the graft decreased in time. Bone tissue loss was about 24%. In contrast, the MB group showed bone tissue gain along the observation period (MB0 = 1.54, MB45 = 2.40, F = 7.91 > FC = 3.02), meaning that the total volume of newly formed bone was greater than the original graft area. Bone tissue gain was approximately 55%. MB showed significantly greater bone gain when compared to B (B45 = 1.05, MB45 = 2.40, F = 39.86 > FC = 1.90). These significant differences between B and MB could already be observed after 21 days. Conclusions. The bone block graft underwent resorption at an early healing stage, while additional new bone formation was observed when the bone graft was covered with an e-PTFE membrane. © 2005 Mosby, Inc. All rights reserved.