Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1193

Search results for: computational biology

1193 Sorting Primitives and Genome Rearrangementin Bioinformatics: A Unified Perspective

Authors: Swapnoneel Roy, Minhazur Rahman, Ashok Kumar Thakur

Abstract:

Bioinformatics and computational biology involve the use of techniques including applied mathematics, informatics, statistics, computer science, artificial intelligence, chemistry, and biochemistry to solve biological problems usually on the molecular level. Research in computational biology often overlaps with systems biology. Major research efforts in the field include sequence alignment, gene finding, genome assembly, protein structure alignment, protein structure prediction, prediction of gene expression and proteinprotein interactions, and the modeling of evolution. Various global rearrangements of permutations, such as reversals and transpositions,have recently become of interest because of their applications in computational molecular biology. A reversal is an operation that reverses the order of a substring of a permutation. A transposition is an operation that swaps two adjacent substrings of a permutation. The problem of determining the smallest number of reversals required to transform a given permutation into the identity permutation is called sorting by reversals. Similar problems can be defined for transpositions and other global rearrangements. In this work we perform a study about some genome rearrangement primitives. We show how a genome is modelled by a permutation, introduce some of the existing primitives and the lower and upper bounds on them. We then provide a comparison of the introduced primitives.

Keywords: Sorting Primitives, Genome Rearrangements, Transpositions, Block Interchanges, Strip Exchanges.

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1192 Implementation of an Undergraduate Integrated Biology and Chemistry Course

Authors: Jayson G. Balansag

Abstract:

An integrated biology and chemistry (iBC) course for freshmen college students was developed in University of Delaware. This course will prepare students to (1) become interdisciplinary thinkers in the field of biology and (2) collaboratively work with others from multiple disciplines in the future. This paper documents and describes the implementation of the course. The information gathered from reading literature, classroom observations, and interviews were used to carry out the purpose of this paper. The major goal of the iBC course is to align the concepts between Biology and Chemistry, so that students can draw science concepts from both disciplines which they can apply in their interdisciplinary researches. This course is offered every fall and spring semesters of each school year. Students enrolled in Biology are also enrolled in Chemistry during the same semester. The iBC is composed of lectures, laboratories, studio sessions, and workshops and is taught by the faculty from the biology and chemistry departments. In addition, the preceptors, graduate teaching assistants, and studio fellows facilitate the laboratory and studio sessions. These roles are interdependent with each other. The iBC can be used as a model for higher education institutions who wish to implement an integrated biology course.

Keywords: Integrated biology and chemistry, integration, interdisciplinary research, new biology, undergraduate science education.

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1191 Grid Computing in Physics and Life Sciences

Authors: Heinz Stockinger

Abstract:

Certain sciences such as physics, chemistry or biology, have a strong computational aspect and use computing infrastructures to advance their scientific goals. Often, high performance and/or high throughput computing infrastructures such as clusters and computational Grids are applied to satisfy computational needs. In addition, these sciences are sometimes characterised by scientific collaborations requiring resource sharing which is typically provided by Grid approaches. In this article, I discuss Grid computing approaches in High Energy Physics as well as in bioinformatics and highlight some of my experience in both scientific domains.

Keywords: Grid computing, Web services, physics, bioinformatics

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1190 Gender Differences in Biology Academic Performances among Foundation Students of PERMATApintar® National Gifted Center

Authors: N. Nor Azman, M. F. Kamarudin, S. I. Ong, N. Maaulot

Abstract:

PERMATApintar® National Gifted Center is, to the author’s best of knowledge, the first center in Malaysia that provides a platform for Malaysian talented students with high ability in thinking. This center has built a teaching and learning biology curriculum that suits the ability of these gifted students. The level of PERMATApintar® biology curriculum is basically higher than the national biology curriculum. Here, the foundation students are exposed to the PERMATApintar® biology curriculum at the age of as early as 11 years old. This center practices a 4-time-a-year examination system to monitor the academic performances of the students. Generally, most of the time, male students show no or low interest towards biology subject compared to female students. This study is to investigate the association of students’ gender and their academic performances in biology examination. A total of 39 students’ scores in twelve sets of biology examinations in 3 years have been collected and analyzed by using the statistical analysis. Based on the analysis, there are no significant differences between male and female students against the biology academic performances with a significant level of p = 0.05. This indicates that gender is not associated with the scores of biology examinations among the students. Another result showed that the average score for male studenta was higher than the female students. Future research can be done by comparing the biology academic achievement in Malaysian National Examination (Sijil Pelajaran Malaysia, SPM) between the Foundation 3 students (Grade 9) and Level 2 students (Grade 11) with similar PERMATApintar® biology curriculum.

Keywords: Academic performances, biology, gender differences, gifted students.

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1189 Virtual Laboratory for Learning Biology – A Preliminary Investigation

Authors: Murniza Muhamad, Halimah Badioze Zaman, Azlina Ahmad

Abstract:

This study aims to conduct a preliminary investigation to determine the topic to be focused in developing Virtual Laboratory For Biology (VLab-Bio). Samples involved in answering the questionnaire are form five students (equivalent to A-Level) and biology teachers. Time and economical resources for the setting up and construction of scientific laboratories can be solved with the adaptation of virtual laboratories as an educational tool. Thus, it is hoped that the proposed virtual laboratory will help students to learn the abstract concepts in biology. Findings show that the difficult topic chosen is Cell Division and the learning objective to be focused in developing the virtual lab is “Describe the application of knowledge on mitosis in cloning".

Keywords: biology education, computer simulation, virtual laboratory, virtual reality

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1188 The Meaning and Structure of Ecological Education of Biology Specialists in Kazakhstan

Authors: E. Tazabekova, B. Amirasheva, L. Amirasheva

Abstract:

This article examines the nature and structure of ecological education of biology specialists in Kazakhstan. Also characterizes the ecological education in high school and specific features in training of biology specialists.

Keywords: Ecological education, environment.

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1187 Protein-Protein Interaction Detection Based on Substring Sensitivity Measure

Authors: Nazar Zaki, Safaai Deris, Hany Alashwal

Abstract:

Detecting protein-protein interactions is a central problem in computational biology and aberrant such interactions may have implicated in a number of neurological disorders. As a result, the prediction of protein-protein interactions has recently received considerable attention from biologist around the globe. Computational tools that are capable of effectively identifying protein-protein interactions are much needed. In this paper, we propose a method to detect protein-protein interaction based on substring similarity measure. Two protein sequences may interact by the mean of the similarities of the substrings they contain. When applied on the currently available protein-protein interaction data for the yeast Saccharomyces cerevisiae, the proposed method delivered reasonable improvement over the existing ones.

Keywords: Protein-Protein Interaction, support vector machine, feature extraction, pairwise alignment, Smith-Waterman score.

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1186 Biologically Inspired Artificial Neural Cortex Architecture and its Formalism

Authors: Alexei M. Mikhailov

Abstract:

The paper attempts to elucidate the columnar structure of the cortex by answering the following questions. (1) Why the cortical neurons with similar interests tend to be vertically arrayed forming what is known as cortical columns? (2) How to describe the cortex as a whole in concise mathematical terms? (3) How to design efficient digital models of the cortex?

Keywords: Cortex, pattern recognition, artificial neural cortex, computational biology, brain and neural engineering.

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1185 Inverse Sets-based Recognition of Video Clips

Authors: Alexei M. Mikhailov

Abstract:

The paper discusses the mathematics of pattern indexing and its applications to recognition of visual patterns that are found in video clips. It is shown that (a) pattern indexes can be represented by collections of inverted patterns, (b) solutions to pattern classification problems can be found as intersections and histograms of inverted patterns and, thus, matching of original patterns avoided.

Keywords: Artificial neural cortex, computational biology, data mining, pattern recognition.

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1184 Breeding Biology and Induced Breeding Status of Freshwater Mud Eel, Monopterus cuchia

Authors: M. F. Miah, H. Ali, E. Zannath, T. M. Shuvra, M. N. Naser, M. K. Ahmed

Abstract:

In this study, breeding biology and induced breeding of freshwater mud eel, Monopterus cuchia was observed during the experimental period from February to June, 2013. Breeding biology of freshwater mud eel, Monopterus cuchia was considered in terms of gonadosomatic index, length-weight relationship of gonad, ova diameter and fecundity. The ova diameter was recorded from 0.3 mm to 4.30 mm and the individual fecundity was recorded from 155 to 1495 while relative fecundity was found from 2.64 to 12.45. The fecundity related to body weight and length of fish was also discussed. A peak of GSI was observed 2.14±0.2 in male and 5.1 ±1.09 in female. Induced breeding of freshwater mud eel, Monopterus cuchia was also practiced with different doses of different inducing agents like pituitary gland (PG), human chorionic gonadotropin (HCG), Gonadotropin releasing hormone (GnRH) and Ovuline-a synthetic hormone in different environmental conditions. However, it was observed that the artificial breeding of freshwater mud eel, Monopterus cuchia was not yet succeeded through inducing agents in captive conditions, rather the inducing agent showed negative impacts on fecundity and ovarian tissues. It was seen that mature eggs in the oviduct were reduced, absorbed and some eggs were found in spoiled condition.

Keywords: Breeding biology, induced breeding, Monopterus cuchia.

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1183 An Empirical Study of the Effect of Robot Programming Education on the Computational Thinking of Young Children: The Role of Flowcharts

Authors: Wei Sun, Yan Dong

Abstract:

There is an increasing interest in introducing computational thinking at an early age. Computational thinking, like mathematical thinking, engineering thinking, and scientific thinking, is a kind of analytical thinking. Learning computational thinking skills is not only to improve technological literacy, but also allows learners to equip with practicable skills such as problem-solving skills. As people realize the importance of computational thinking, the field of educational technology faces a problem: how to choose appropriate tools and activities to help students develop computational thinking skills. Robots are gradually becoming a popular teaching tool, as robots provide a tangible way for young children to access to technology, and controlling a robot through programming offers them opportunities to engage in developing computational thinking. This study explores whether the introduction of flowcharts into the robotics programming courses can help children convert natural language into a programming language more easily, and then to better cultivate their computational thinking skills. An experimental study was adopted with a sample of children ages six to seven (N = 16) participated, and a one-meter-tall humanoid robot was used as the teaching tool. Results show that children can master basic programming concepts through robotic courses. Children's computational thinking has been significantly improved. Besides, results suggest that flowcharts do have an impact on young children’s computational thinking skills development, but it only has a significant effect on the "sequencing" and "correspondence" skills. Overall, the study demonstrates that the humanoid robot and flowcharts have qualities that foster young children to learn programming and develop computational thinking skills.

Keywords: Robotics, computational thinking, programming, young children, flowcharts.

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1182 Web–Based Tools and Databases for Micro-RNA Analysis: A Review

Authors: Sitansu Kumar Verma, Soni Yadav, Jitendra Singh, Shraddha, Ajay Kumar

Abstract:

MicroRNAs (miRNAs), a class of approximately 22 nucleotide long non coding RNAs which play critical role in different biological processes. The mature microRNA is usually 19–27 nucleotides long and is derived from a bigger precursor that folds into a flawed stem-loop structure. Mature micro RNAs are involved in many cellular processes that encompass development, proliferation, stress response, apoptosis, and fat metabolism by gene regulation. Resent finding reveals that certain viruses encode their own miRNA that processed by cellular RNAi machinery. In recent research indicate that cellular microRNA can target the genetic material of invading viruses. Cellular microRNA can be used in the virus life cycle; either to up regulate or down regulate viral gene expression Computational tools use in miRNA target prediction has been changing drastically in recent years. Many of the methods have been made available on the web and can be used by experimental researcher and scientist without expert knowledge of bioinformatics. With the development and ease of use of genomic technologies and computational tools in the field of microRNA biology has superior tremendously over the previous decade. This review attempts to give an overview over the genome wide approaches that have allow for the discovery of new miRNAs and development of new miRNA target prediction tools and databases.

Keywords: MicroRNAs, computational tools, gene regulation, databases, RNAi.

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1181 Dataset Analysis Using Membership-Deviation Graph

Authors: Itgel Bayarsaikhan, Jimin Lee, Sejong Oh

Abstract:

Classification is one of the primary themes in computational biology. The accuracy of classification strongly depends on quality of a dataset, and we need some method to evaluate this quality. In this paper, we propose a new graphical analysis method using 'Membership-Deviation Graph (MDG)' for analyzing quality of a dataset. MDG represents degree of membership and deviations for instances of a class in the dataset. The result of MDG analysis is used for understanding specific feature and for selecting best feature for classification.

Keywords: feature, classification, machine learning algorithm.

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1180 A Computational Stochastic Modeling Formalism for Biological Networks

Authors: Werner Sandmann, Verena Wolf

Abstract:

Stochastic models of biological networks are well established in systems biology, where the computational treatment of such models is often focused on the solution of the so-called chemical master equation via stochastic simulation algorithms. In contrast to this, the development of storage-efficient model representations that are directly suitable for computer implementation has received significantly less attention. Instead, a model is usually described in terms of a stochastic process or a "higher-level paradigm" with graphical representation such as e.g. a stochastic Petri net. A serious problem then arises due to the exponential growth of the model-s state space which is in fact a main reason for the popularity of stochastic simulation since simulation suffers less from the state space explosion than non-simulative numerical solution techniques. In this paper we present transition class models for the representation of biological network models, a compact mathematical formalism that circumvents state space explosion. Transition class models can also serve as an interface between different higher level modeling paradigms, stochastic processes and the implementation coded in a programming language. Besides, the compact model representation provides the opportunity to apply non-simulative solution techniques thereby preserving the possible use of stochastic simulation. Illustrative examples of transition class representations are given for an enzyme-catalyzed substrate conversion and a part of the bacteriophage λ lysis/lysogeny pathway.

Keywords: Computational Modeling, Biological Networks, Stochastic Models, Markov Chains, Transition Class Models.

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1179 Exploring Dimensionality, Systematic Mutations and Number of Contacts in Simple HP ab-initio Protein Folding Using a Blackboard-based Agent Platform

Authors: Hiram I. Beltrán, Arturo Rojo-Domínguez, Máximo Eduardo Sánchez Gutiérrez, Pedro Pablo González Pérez

Abstract:

A computational platform is presented in this contribution. It has been designed as a virtual laboratory to be used for exploring optimization algorithms in biological problems. This platform is built on a blackboard-based agent architecture. As a test case, the version of the platform presented here is devoted to the study of protein folding, initially with a bead-like description of the chain and with the widely used model of hydrophobic and polar residues (HP model). Some details of the platform design are presented along with its capabilities and also are revised some explorations of the protein folding problems with different types of discrete space. It is also shown the capability of the platform to incorporate specific tools for the structural analysis of the runs in order to understand and improve the optimization process. Accordingly, the results obtained demonstrate that the ensemble of computational tools into a single platform is worthwhile by itself, since experiments developed on it can be designed to fulfill different levels of information in a self-consistent fashion. By now, it is being explored how an experiment design can be useful to create a computational agent to be included within the platform. These inclusions of designed agents –or software pieces– are useful for the better accomplishment of the tasks to be developed by the platform. Clearly, while the number of agents increases the new version of the virtual laboratory thus enhances in robustness and functionality.

Keywords: genetic algorithms, multi-agent systems, bioinformatics, optimization, protein folding, structural biology.

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1178 Modular Workflow System for HPC Applications

Authors: Y. Yudin, T. Krasikova, Y. Dorozhko, N. Currle-Linde

Abstract:

Nowadays, HPC, Grid and Cloud systems are evolving very rapidly. However, the development of infrastructure solutions related to HPC is lagging behind. While the existing infrastructure is sufficient for simple cases, many computational problems have more complex requirements.Such computational experiments use different resources simultaneously to start a large number of computational jobs.These resources are heterogeneous. They have different purposes, architectures, performance and used software.Users need a convenient tool that allows to describe and to run complex computational experiments under conditions of HPC environment. This paper introduces a modularworkflow system called SEGL which makes it possible to run complex computational experiments under conditions of a real HPC organization. The system can be used in a great number of organizations, which provide HPC power. Significant requirements to this system are high efficiency and interoperability with the existing HPC infrastructure of the organization without any changes.

Keywords: HPC, Molecular Dynamics, Workflow Languages, Workflow Management.

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1177 Modeling Biology Inspired Reactive Agents Using X-machines

Authors: George Eleftherakis, Petros Kefalas, Anna Sotiriadou, Evangelos Kehris

Abstract:

Recent advances in both the testing and verification of software based on formal specifications of the system to be built have reached a point where the ideas can be applied in a powerful way in the design of agent-based systems. The software engineering research has highlighted a number of important issues: the importance of the type of modeling technique used; the careful design of the model to enable powerful testing techniques to be used; the automated verification of the behavioural properties of the system; the need to provide a mechanism for translating the formal models into executable software in a simple and transparent way. This paper introduces the use of the X-machine formalism as a tool for modeling biology inspired agents proposing the use of the techniques built around X-machine models for the construction of effective, and reliable agent-based software systems.

Keywords: Biology inspired agent, formal methods, x-machines.

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1176 Computational Fluid Dynamics Expert System using Artificial Neural Networks

Authors: Gonzalo Rubio, Eusebio Valero, Sven Lanzan

Abstract:

The design of a modern aircraft is based on three pillars: theoretical results, experimental test and computational simulations. As a results of this, Computational Fluid Dynamic (CFD) solvers are widely used in the aeronautical field. These solvers require the correct selection of many parameters in order to obtain successful results. Besides, the computational time spent in the simulation depends on the proper choice of these parameters. In this paper we create an expert system capable of making an accurate prediction of the number of iterations and time required for the convergence of a computational fluid dynamic (CFD) solver. Artificial neural network (ANN) has been used to design the expert system. It is shown that the developed expert system is capable of making an accurate prediction the number of iterations and time required for the convergence of a CFD solver.

Keywords: Artificial Neural Network, Computational Fluid Dynamics, Optimization

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1175 Alternative Computational Arrangements on g-Group (g > 2) Profile Analysis

Authors: Emmanuel U. Ohaegbulem, Felix N. Nwobi

Abstract:

Alternative and simple computational arrangements in carrying out multivariate profile analysis when more than two groups (populations) are involved are presented. These arrangements have been demonstrated to not only yield equivalent results for the test statistics (the Wilks lambdas), but they have less computational efforts relative to other arrangements so far presented in the literature; in addition to being quite simple and easy to apply.

Keywords: Coincident profiles, g-group profile analysis, level profiles, parallel profiles, repeated measures MANOVA.

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1174 Application of Agile Project Methodology in Computational Fluid Dynamics Engineering Project

Authors: Mohammed Bilal, Noor Hyder

Abstract:

Agile methodology is a popular project management methodology and is widely used in many engineering projects. In the recent years agile methodology is successful in countering the inherent problems seen in traditional methodology. The application of the Agile methodology in the computational fluid dynamic project had improved the project delivery performance. Computational Fluid Dynamics (CFD) is the method to solve and analyze the fluid flow problems by the application of the numerical analysis. In this paper, study is conducted using agile methodology and results are compared with waterfall methodology. The result shows that the agile methodology is improves the final delivery of the project.

Keywords: Agile methodology, traditional methodology, engineering management, engineering technology, Computational Fluid Dynamics, project management.

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1173 Design of Experiment and Computational Fluid Dynamics Used to Optimize Hydrodynamic Characteristics of the Marine Propeller

Authors: Rohit Suryawanshi

Abstract:

In this study, the commercial Computational Fluid Dynamics (CFD), ANSYS-Fluent, has been used to optimize the marine propeller with the design of experiment (DOE) method. At the initial stage, different propeller parameters ware selected for the three different levels. The four characteristics factors are: no. of the blade, camber value, pitch delta & chord at the hub. Then, CAD modelling is performed by considering the selected factor and level. In this investigation, a total of 9 test models are simulated with the Reynolds-Averaged Navier-Stokes (RANS) equations. The standard, realizable

Keywords: Marine propeller, Computational Fluid Dynamics, optimization, DOE, propeller thrust.

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1172 A Computational Model of Minimal Consciousness Functions

Authors: Nabila Charkaoui

Abstract:

Interest in Human Consciousness has been revived in the late 20th century from different scientific disciplines. Consciousness studies involve both its understanding and its application. In this paper, a computational model of the minimum consciousness functions necessary in my point of view for Artificial Intelligence applications is presented with the aim of improving the way computations will be made in the future. In section I, human consciousness is briefly described according to the scope of this paper. In section II, a minimum set of consciousness functions is defined - based on the literature reviewed - to be modelled, and then a computational model of these functions is presented in section III. In section IV, an analysis of the model is carried out to describe its functioning in detail.

Keywords: Consciousness, perception, attention.

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1171 The Multimedia Interactive Theatre by Virtual Means Regarding Computational Intelligence in Space Design as HCI and Samples from Turkey

Authors: Pelin Yildiz

Abstract:

The aim of this study is to emphasize the opportunities in space design under the aspect of HCI as performance areas. HCI is a multidisciplinary approach that could be identified in many different areas. The aesthetical reflections of HCI by virtual reality in space design are the high-tech solutions of the new innovations as computational facilities by artistic features. The method of this paper is to identify the subject in 3 main parts. In the first part a general approach and definition of interactivity on the basis of space design; in the second part the concept of multimedia interactive theater by some chosen samples from the world and interactive design aspects; in the third part the samples from Turkey will be identified by stage designing principles. In the results it could be declared that the multimedia database is the virtual approach of theatre stage designing regarding interactive means by computational facilities according to aesthetical aspects. HCI is mostly identified in theatre stages as computational intelligence under the affect of interactivity.

Keywords: Computational intelligence, interactive space, multimedia theatre, virtual reality.

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1170 Continuum-Based Modelling Approaches for Cell Mechanics

Authors: Yogesh D. Bansod, Jiri Bursa

Abstract:

The quantitative study of cell mechanics is of paramount interest, since it regulates the behaviour of the living cells in response to the myriad of extracellular and intracellular mechanical stimuli. The novel experimental techniques together with robust computational approaches have given rise to new theories and models, which describe cell mechanics as combination of biomechanical and biochemical processes. This review paper encapsulates the existing continuum-based computational approaches that have been developed for interpreting the mechanical responses of living cells under different loading and boundary conditions. The salient features and drawbacks of each model are discussed from both structural and biological points of view. This discussion can contribute to the development of even more precise and realistic computational models of cell mechanics based on continuum approaches or on their combination with microstructural approaches, which in turn may provide a better understanding of mechanotransduction in living cells.

Keywords: Cell mechanics, computational models, continuum approach, mechanical models.

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1169 All-or-None Principle and Weakness of Hodgkin-Huxley Mathematical Model

Authors: S. A. Sadegh Zadeh, C. Kambhampati

Abstract:

Mathematical and computational modellings are the necessary tools for reviewing, analysing, and predicting processes and events in the wide spectrum range of scientific fields. Therefore, in a field as rapidly developing as neuroscience, the combination of these two modellings can have a significant role in helping to guide the direction the field takes. The paper combined mathematical and computational modelling to prove a weakness in a very precious model in neuroscience. This paper is intended to analyse all-or-none principle in Hodgkin-Huxley mathematical model. By implementation the computational model of Hodgkin-Huxley model and applying the concept of all-or-none principle, an investigation on this mathematical model has been performed. The results clearly showed that the mathematical model of Hodgkin-Huxley does not observe this fundamental law in neurophysiology to generating action potentials. This study shows that further mathematical studies on the Hodgkin-Huxley model are needed in order to create a model without this weakness.

Keywords: All-or-none, computational modelling, mathematical model, transmembrane voltage, action potential.

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1168 Observation of the Correlations between Pair Wise Interaction and Functional Organization of the Proteins, in the Protein Interaction Network of Saccaromyces Cerevisiae

Authors: N. Tuncbag, T. Haliloglu, O. Keskin

Abstract:

Understanding the cell's large-scale organization is an interesting task in computational biology. Thus, protein-protein interactions can reveal important organization and function of the cell. Here, we investigated the correspondence between protein interactions and function for the yeast. We obtained the correlations among the set of proteins. Then these correlations are clustered using both the hierarchical and biclustering methods. The detailed analyses of proteins in each cluster were carried out by making use of their functional annotations. As a result, we found that some functional classes appear together in almost all biclusters. On the other hand, in hierarchical clustering, the dominancy of one functional class is observed. In brief, from interaction data to function, some correlated results are noticed about the relationship between interaction and function which might give clues about the organization of the proteins.

Keywords: Pair-wise protein interactions, DIP database, functional correlations, biclustering.

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1167 Performance Assessment of Computational Gridon Weather Indices from HOAPS Data

Authors: Madhuri Bhavsar, Anupam K Singh, Shrikant Pradhan

Abstract:

Long term rainfall analysis and prediction is a challenging task especially in the modern world where the impact of global warming is creating complications in environmental issues. These factors which are data intensive require high performance computational modeling for accurate prediction. This research paper describes a prototype which is designed and developed on grid environment using a number of coupled software infrastructural building blocks. This grid enabled system provides the demanding computational power, efficiency, resources, user-friendly interface, secured job submission and high throughput. The results obtained using sequential execution and grid enabled execution shows that computational performance has enhanced among 36% to 75%, for decade of climate parameters. Large variation in performance can be attributed to varying degree of computational resources available for job execution. Grid Computing enables the dynamic runtime selection, sharing and aggregation of distributed and autonomous resources which plays an important role not only in business, but also in scientific implications and social surroundings. This research paper attempts to explore the grid enabled computing capabilities on weather indices from HOAPS data for climate impact modeling and change detection.

Keywords: Climate model, Computational Grid, GridApplication, Heterogeneous Grid

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1166 A Fast, Portable Computational Framework for Aerodynamic Simulations

Authors: Mehdi Ghommem, Daniel Garcia, Nathan Collier, Victor Calo

Abstract:

We develop a fast, user-friendly implementation of a potential flow solver based on the unsteady vortex lattice method (UVLM). The computational framework uses the Python programming language which has easy integration with the scripts requiring computationally-expensive operations written in Fortran. The mixed-language approach enables high performance in terms of solution time and high flexibility in terms of easiness of code adaptation to different system configurations and applications. This computational tool is intended to predict the unsteady aerodynamic behavior of multiple moving bodies (e.g., flapping wings, rotating blades, suspension bridges...) subject to an incoming air. We simulate different aerodynamic problems to validate and illustrate the usefulness and effectiveness of the developed computational tool.

Keywords: Unsteady aerodynamics, numerical simulations, mixed-language approach, potential flow.

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1165 Big Data Analytics and Data Security in the Cloud via Fully Homomorphic Encryption

Authors: Victor Onomza Waziri, John K. Alhassan, Idris Ismaila, Moses Noel Dogonyaro

Abstract:

This paper describes the problem of building secure computational services for encrypted information in the Cloud Computing without decrypting the encrypted data; therefore, it meets the yearning of computational encryption algorithmic aspiration model that could enhance the security of big data for privacy, confidentiality, availability of the users. The cryptographic model applied for the computational process of the encrypted data is the Fully Homomorphic Encryption Scheme. We contribute a theoretical presentations in a high-level computational processes that are based on number theory and algebra that can easily be integrated and leveraged in the Cloud computing with detail theoretic mathematical concepts to the fully homomorphic encryption models. This contribution enhances the full implementation of big data analytics based cryptographic security algorithm.

Keywords: Data Analytics, Security, Privacy, Bootstrapping, and Fully Homomorphic Encryption Scheme.

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1164 CFD Simulation of the Hydrodynamic Vibrator for Stuck - Pipe Liquidation

Authors: L. Grinis, V. Haslavsky

Abstract:

Stuck-pipe in drilling operations is one of the most pressing and expensive problems in the oil industry. This paper describes a computational simulation and an experimental study of the hydrodynamic vibrator, which may be used for liquidation of stuck-pipe problems during well drilling. The work principle of the vibrator is based upon the known phenomena of Vortex Street of Karman and the resulting generation of vibrations. We will discuss the computational simulation and experimental investigations of vibrations in this device. The frequency of the vibration parameters has been measured as a function of the wide range Reynolds Number. The validity of the computational simulation and of the assumptions on which it is based has been proved experimentally. The computational simulation of the vibrator work and its effectiveness was carried out using FLUENT software. The research showed high degree of congruence with the results of the laboratory tests and allowed to determine the effect of the granular material features upon the pipe vibration in the well. This study demonstrates the potential of using the hydrodynamic vibrator in a well drilling system.

Keywords: Drilling, stuck-pipe, vibration, vortex shedding.

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