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Proceedings of the 16th Annual UT-KBRIN Bioinformatics Summit 2016: bioinformatics

BMC Bioinformatics 2017年第9期18卷 1-9页

作者： Eric C. Rouchka Juw Won Park Julia H. Chariker David A. Tieri Shreedharkumar Rajurkar Vikas Singh Nishchal K. Verma Yan Cui Mark Farman Bradford Condon Jolanta Jaromczyk Neil Moore Jerzy Jaromczyk Daniel Harris Patrick Calie Eun Kyong Shin Robert L. Davis Arash Shaban-Nejad Joshua M. Mitchell Hunter N. B. Moseley Robert M. Flight Qing Jun Wang Richard M. Higashi Teresa W-M Fan Andrew N. Lane Liangqun Lu Bernie J Daigle Jr. Xi Chen Andrey Smelter Jerzy W. Jaromczyk Bailey K. Phan Nathaniel J. Serpico Ethan G. Toney Li Chen Caroline E. Melton Jennifer R. Mandel Bernie J. Daigle Jr. Hao Chen Kazi I. Zaman Ramin Homayouni Patrick J. Trainor Andrew P. DeFilippis Samantha M. Carlisle Shesh N. Rai Department of Computer Engineering and Computer Science University of Louisville Duthie Center for Engineering Louisville KY 40292 USA Kentucky Biomedical Research Infrastructure (KBRIN) Bioinformatics Core 522 East Gray Street Louisville KY 40292 USA Department of Psychological and Brain Sciences University of Louisville Louisville KY 40292 USA Department of Anatomical Sciences and Neurobiology University of Louisville Louisville KY 40292 USA Department of Electrical Engineering IIT Kanpur India Department of Microbiology Immunology and Biochemistry University of Tennessee Health Science Center Memphis TN 38103 USA Center for Integrative and Translational Genomics University of Tennessee Health Science Center Memphis TN 38103 USA Department of Plant Pathology University of Kentucky Lexington KY 40546 USA UK Healthcare Genomics University of Kentucky Lexington KY 40536 USA Department of Entomology & Plant Pathology University of Tennessee Knoxville TN 37996 USA Department of Forestry University of Kentucky Lexington KY 40506 USA Department of Computer Science University of Kentucky Lexington KY 40506 USA Department of Computer Science University of Kentucky Lexington KY 40508 USA Department of Biological Sciences Eastern Kentucky University Richmond KY 40475 USA University of Tennessee Health Science Center – Oak-Ridge National Lab (UTHSC-ORNL) Center for Biomedical Informatics Department of Pediatrics Memphis TN 38103 USA Department of Molecular & Cellular Biochemistry University of Kentucky Lexington KY 40536 USA Markey Cancer Center University of Kentucky Lexington KY 40536 USA Center for Environmental and Systems Biochemistry University of Kentucky Lexington KY 40536 USA Institute for Biomedical Informatics University of Kentucky Lexington KY 40536 USA Department of Molecular and Cellular Biochemistry University of Kentucky Lexington KY 40536 USA Department of Statistics University of Kentucky Louisville KY

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Dynamic Cloud Resources Allocation on Multidomain/Multiphysics Problems

Dynamic Cloud Resources Allocation on Multidomain/Multiphysi...

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International Conference on Future Internet of Things and Cloud (FiCloud)

作者： Niki Sfika Aigli Korfiati Christos Alexakos Spiros Likothanassis Konstantis Daloukas Panagiota Tsompanopoulou Department of Computer Engineering and Informatics University of Patras Patras Greece Department of Electrical and Computer Engineering University of Thessaly Volos Greece

The solution of multidomain/multiphysics problems is a computationally and memory demanding process, especially for large-scale differential equations. In this paper, we propose a cloud application that provides users a solution environment for multiphysics/multidomain problems utilizing cloud technologies that manage pre-existing hardware, network, operating system and applications. Particularly, according to the problem and its computational demands, the user can have the results from any place and any device without any other concern. The user sets the problem's parameters, chooses the solution method that fits better to the specific problem and finally gets the problem solution. The application dynamically allocates the minimum possible resources automatically in the background without the user's interference.

关键词： Cloud computing Monitoring Computational modeling computers Schedules Resource management

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Generalized Force-and-Energy Manipulability for design and control of redundant robotic arm

Generalized Force-and-Energy Manipulability for design and c...

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IEEE/RSJ International Conference on Intelligent Robots and Systems

作者： D. Mori G. Ishigami Data and Software Engineering Research Group School of Electrical Engineering and Informatics ITB Bandung Indonesia Department of Computer Engineering and Informatics Bandung State Polytechnics Bandung

There is a possibility of remaining indication of microorganisms on Martian subsurface and therefore, a robotic arm mounted on an exploration robot is required to dig to a certain depth and collect appropriate sample to be analyzed. However, the environment on the surface of Mars is harsh and most of all, limited power is available from the solar panel. In this paper, FEMI (Force-and-Energy Manipulability Index) is proposed to evaluate a feasible arm configuration for low energy consumption in its soil sampling operation. FEMI is calculated by the combination of an energy manipulability of an arm and an external force generated at an end effector of the arm. The FEMI derives the most feasible configuration on the joint angles of the arm for each sampling point. The usefulness of the FEMI is confirmed through a numerical simulation of a robotic arm. The simulation also presents that the FEMI can be used to obtain mechanical parameters of the arm such as link length and motor power, that are optimally-designed for a certain mission.

关键词： Robots Soil Gravity Ellipsoids Mathematical model Energy consumption

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A software system family: Learning from simple data processing to knowledge management system of research

A software system family: Learning from simple data processi...

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International Conference on Information Technology and electrical engineering (ICITEE)

作者： Inggriani Liem Transmissia Semiawan Ade Chandra Suprihanto Data and Software Engineering Research Group School of Electrical Engineering and Informatics ITB Bandung Indonesia Department of Computer Engineering and Informatics Bandung State Polytechnics Bandung

In this paper, we propose a series of applications that represent a system family for processing Research Data. The whole system is a model of complete data flow of "research", from data capturing, processing, until intelligent data analysis. Data engineering, Software engineering, Domain engineering and Ontology engineering are used for the development of the system. We also described tools and technologies to be used in building the system. The prototype of a small scale system has been built as a proof of concept of this family of system, for the domain of "Research" in Indonesian context. The aim of building this prototype are: (a) to provide an architectural description prototype of a knowledge repository where Indonesian Context Research as a central domain (b) to comprehend a software engineering for software system family.

关键词： Ontologies Software Data models Unified modeling language Prototypes Software engineering Information systems

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Preservation and interconnection of iISS and ISS dissipation inequalities by scaling

Preservation and interconnection of iISS and ISS dissipation...

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作者： Ito, Hiroshi Kellett, Christopher M. Department of Systems Design and Informatics Kyushu Institute of Technology Iizuka Fukuoka820-8502 Japan School of Electrical Engineering and Computer Science The University of Newcastle CallaghanNew South Wales2308 Australia

Scaling of Lyapunov functions has been a central tool in analysis and design of nonlinear systems. In this paper, the essence of some scaling techniques used extensively in the literature is reformulated in view of preservation of dissipation inequalities of integral input-to-state stability (iISS) and input-to-state stability (ISS). The iISS small-gain theorem is revisited from this viewpoint. Preservation of ISS dissipation inequalities is shown to not always be necessary, while preserving iISS which is weaker than ISS is convenient. By establishing relationships between the Legendre-Fenchel transform and the reformulated scaling techniques, this paper proposes a way to construct less complicated Lyapunov functions for interconnected systems. © 2015

关键词： Lyapunov methods

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DOMMINO 2.0: Integrating structurally resolved protein-, RNA-, and DNA-mediated Macromolecular interactions

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Database 2016年第2016期2016卷 bav114页

作者： Kuang, Xingyan Dhroso, Andi Han, Jing Ginger Shyu, Chi-Ren Korkin, Dmitry Informatics Institute University of Missouri Columbia MO United States Department of Computer Science Bioinformatics and Computational Biology Program Worcester Polytechnic Institute Worcester MA United States Department of Electrical and Computer Engineering United States Department of Computer Science University of Missouri Columbia MO United States Ohio State University Comprehensive Cancer Center Columbus OH United States

Macromolecular interactions are formed between proteins, DNA and RNA molecules. Being a principle building block in macromolecular assemblies and pathways, the interactions underlie most of cellular functions. Malfunctioning of macromolecular interactions is also linked to a number of diseases. Structural knowledge of the macromolecular interaction allows one to understand the interaction's mechanism, determine its functional implications and characterize the effects of genetic variations, such as single nucleotide polymorphisms, on the interaction. Unfortunately, until now the interactions mediated by different types of macromolecules, e.g. protein-protein interactions or protein-DNA interactions, are collected into individual and unrelated structural databases. This presents a significant obstacle in the analysis of macromolecular interactions. For instance, the homogeneous structural interaction databases prevent scientists from studying structural interactions of different types but occurring in the same macromolecular complex. Here, we introduce DOMMINO 2.0, a structural Database Of Macro-Molecular INteractiOns. Compared to DOMMINO 1.0, a comprehensive database on protein-protein interactions, DOMMINO 2.0 includes the interactions between all three basic types of macromolecules extracted from PDB files. DOMMINO 2.0 is automatically updated on a weekly basis. It currently includes ∼1 040 000 interactions between two polypeptide subunits (e.g. domains, peptides, termini and interdomain linkers), ∼43 000 RNA-mediated interactions, and ∼12 000 DNA-mediated interactions. All protein structures in the database are annotated using SCOP and SUPERFAMILY family annotation. As a result, protein-mediated interactions involving protein domains, interdomain linkers, C- and N-termini, and peptides are identified. Our database provides an intuitive web interface, allowing one to investigate interactions at three different resolution levels: whole subunit network, binary intera

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Automated, high throughput exploration of process–structure–property relationships using the MapReduce paradigm

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Materials Discovery 2015年 1卷 21-28页

作者： Wodo, Olga Zola, Jaroslaw Sarath Pokuri, Balaji Sesha Du, Pengfei Ganapathysubramanian, Baskar University at Buffalo Materials Design and Innovation Department Buffalo United States University at Buffalo Mechanical and Aerospace Engineering Department Buffalo United States University at Buffalo Computational and Data-Enabled Science and Engineering Program Buffalo United States University at Buffalo Computer Science and Engineering Department Buffalo United States University at Buffalo Biomedical Informatics Department Buffalo United States Iowa State University Mechanical Engineering Department Ames United States Iowa State University Electrical and Computer Engineering Department Ames United States

The microstructure of a material intimately affects the performance of a device made from this material. The microstructure, in turn, is affected by the processing pathway used to fabricate the device. This forms the process–structure–property triangle that is central to material science. There has been increasing interest to comprehensively understand and subsequently exploit process–structure–property (PSP) relationships to design processing pathways that result in tailored microstructures exhibiting optimal properties. However, unraveling process–structure–property relationships usually requires systematic and tedious combinatorial search of process and system variables to identify the microstructures that are produced. This is further complicated by the necessity to interrogate the properties of the huge set of corresponding microstructures. Motivated by this challenge, we focus on developing a generic methodology to establish and explore PSP pathways. We leverage recent advances in high performance computing (HPC) and high throughput computing (HTC) with the premise that a domain expert should be able to focus on domain specific PSP problems while the highly specialized HPC/HTC knowledge needed to approach such problems should be hidden from the domain expert. Our hypothesis is that PSP exploration can be naturally formulated in terms of a standard paradigm in cloud computing, namely the MapReduce programming model. We show how reformulating PSP exploration into a MapReduce workflow enables us to take advantage of advances in cloud computing while requiring minimal specialized knowledge of HPC. We illustrate this generic approach by exploring PSP relationships relevant to organic photovoltaics. We focus on identifying microstructural traits that correlate with specific properties of the photovoltaic process: exciton generation, exciton dissociation and charge generation. We integrate a graph-based microstructure characterization tool, and a microstructure-aware

关键词： Drift diffusion model High throughput analysis MapReduce paradigm Organic solar cells Process–structure–processing Thermal annealing

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Network geometry inference using common neighbors

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Physical Review E 2015年第2期92卷 022807-022807页

作者： Fragkiskos Papadopoulos Rodrigo Aldecoa Dmitri Krioukov Department of Electrical Engineering Computer Engineering and Informatics Cyprus University of Technology Saripolou 33 Limassol 3036 Cyprus Northeastern University Department of Physics Boston Massachusetts 02115 USA Northeastern University Department of Physics Department of Mathematics Department of Electrical & Computer Engineering Boston Massachusetts 02115 USA

We introduce and explore a method for inferring hidden geometric coordinates of nodes in complex networks based on the number of common neighbors between the nodes. We compare this approach to the HyperMap method, which is based only on the connections (and disconnections) between the nodes, i.e., on the links that the nodes have (or do not have). We find that for high degree nodes, the common-neighbors approach yields a more accurate inference than the link-based method, unless heuristic periodic adjustments (or “correction steps”) are used in the latter. The common-neighbors approach is computationally intensive, requiring O(t4) running time to map a network of t nodes, versus O(t3) in the link-based method. But we also develop a hybrid method with O(t3) running time, which combines the common-neighbors and link-based approaches, and we explore a heuristic that reduces its running time further to O(t2), without significant reduction in the mapping accuracy. We apply this method to the autonomous systems (ASs) Internet, and we reveal how soft communities of ASs evolve over time in the similarity space. We further demonstrate the method's predictive power by forecasting future links between ASs. Taken altogether, our results advance our understanding of how to efficiently and accurately map real networks to their latent geometric spaces, which is an important necessary step toward understanding the laws that govern the dynamics of nodes in these spaces, and the fine-grained dynamics of network connections.

关键词： COORDINATES GEOMETRY HEURISTIC algorithms FUNCTION spaces MAPPINGS (Mathematics)

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Plane-Sweep Algorithms for the K Group Nearest-Neighbor Query

Plane-Sweep Algorithms for the K Group Nearest-Neighbor Quer...

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International Conference on Geographical Information Systems Theory, Applications and Management

作者： George Roumelis Michael Vassilakopoulos Antonio Corral Yannis Manolopoulos Department of Informatics Aristotle University Department of Electrical and Computer Engineering University of Thessaly Department of Informatics University of Almeria

ISBN: (纸本)9781467384124

One of the most representative and studied queries in Spatial Databases is the (K) Nearest-Neighbor (NNQ), that discovers the (K) nearest neighbor(s) to a query point. An extension that is important for practical applications is the (K) Group Nearest Neighbor Query (GNNQ), that discovers the (K) nearest neighbor(s) to a group of query points (considering the sum of distances to all the members of the query group). This query has been studied during the recent years, considering data sets indexed by efficient spatial data structures. We study (K) GNNQs, considering non-indexed data sets, since this case is frequent in practical applications. And we present two (RAM-based) Plane-Sweep algorithms, that apply optimizations emerging from the geometric properties of the problem. By extensive experimentation, using real and synthetic data sets, we highlight the most efficient algorithm.

关键词： Spatial Query Processing Plane-Sweep Group Nearest-Neighbor Query Algorithms

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Design and Implementation of Natural Language Processing with Syntax and Semantic Analysis for Extract Traffic Conditions from Social Media Data

Design and Implementation of Natural Language Processing wit...

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IEEE International Conference on System engineering and Technology

作者： Mochamad Vicky Ghani Aziz Ary Setijadi Prihatmanto Diotra Henriyan Rifki Wijaya Control and Computer System Laboratory School of Electrical Engineering and Informatics Institut Teknologi Bandung

ISBN: (纸本)9781467367141

Traffic congestion is still a crucial issue because it has a huge impact from the waste of time, the fuel to air pollution. Search information on traffic conditions have been widely available such as through Twitter and the website of CCTV, but the rapid development of online information services resulted in the lack of time to read the complete information. By utilizing the Twitter data, then created a summary regarding the traffic, the summary can improve time efficiency and effectiveness in obtaining information about traffic conditions. However, the structure of the language of Twitter tweets unstructured and raw cause difficult to process information computer, to solve these problems then summarize it using Natural Language Processing approach the syntactic and semantic analysis to improve the structure of words and sentence parsing so that it can classify traffic conditions tweet of the sentence.

关键词： Natural language processing Syntax and semantic analysis Extract traffic condition Natural Language Processing syntax Social Media Traffic TWITTER Language Processing CLOSED CIRCUIT TELEVISION traffic congestion time efficiency Semantics

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