Computer Sciences Commons^™

Dynamic Energy Aware Task Scheduling For Periodic Tasks Using Expected Execution Time Feedback, Sachin Pawaskar, Hesham Ali

Computer Science Faculty Proceedings & Presentations

Scheduling dependent tasks is one of the most challenging problems in parallel and distributed systems. It is known to be computationally intractable in its general form as well as several restricted cases. An interesting application of scheduling is in the area of energy awareness for mobile battery operated devices where minimizing the energy utilized is the most important scheduling policy consideration. A number of heuristics have been developed for this consideration. In this paper, we study the scheduling problem for a particular battery model. In the proposed work, we show how to enhance a well know approach of accounting for …

Semantics And Services Enabled Problem Solving Environment For Trypanosoma Cruzi, Amit P. Sheth, Rick L. Tarleton, Mark Musen, Satya S. Sahoo, Prashant Doshi, Natasha Noy

Kno.e.sis Publications

No abstract provided.

Semantic Sensor Web, Cory Andrew Henson

Kno.e.sis Publications

No abstract provided.

Ontology Driven Semantic Provenance For Heterogeneous Bionomics Experimental Data, Satya S. Sahoo, Michael L. Raymer, Cory Andrew Henson, Amit P. Sheth, William S. York

Kno.e.sis Publications

Scientific experimental data generated by all the bionomic technologies is characterized by heterogeneity in its representation formats, constituents, and generation processes and, therefore, also in its usage. Using the proteomics domain we demonstrate the important role of provenance information o manage, interpret and analyze experimental data. We present a novel approach that employs an ontology as a knowledge model to automatically create semantic provenance information for high-throughput mass spectrometry (MS) data in the glycoproteomics domain. The Semantic Provenance Annotation of Data in protEomics (SPADE) implementation is based on the ProPreO ontology, a large-process ontology ( ~500 classes, 40 named relationships …

Validation Of An Nsp-Based (Negative Selection Pattern) Gene Family Identification Strategy, Ronald L. Frank, Cyriac Kandoth, Fikret Erçal

Biological Sciences Faculty Research & Creative Works

Background: Gene family identification from ESTs can be a valuable resource for analysis of genome evolution but presents unique challenges in organisms for which the entire genome is not yet sequenced. We have developed a novel gene family identification method based on negative selection patterns (NSP) between family members to screen EST-generated contigs. This strategy was tested on five known gene families in Arabidopsis to see if individual paralogs could be identified with accuracy from EST data alone when compared to the actual gene sequences in this fully sequenced genome. Results: The NSP method uniquely identified family members in all …

Cheap Boolean Role Constructors For Description Logics, Sebastian Rudolph, Markus Krotzsch, Pascal Hitzler

Computer Science and Engineering Faculty Publications

We investigate the possibility of incorporating Boolean role constructors on simple roles into some of today's most popular description logics, focussing on cases where those extensions do not increase complexity of reasoning. We show that the expressive DLs SHOIQ and SROIQ, serving as the logical underpinning of OWL and the forthcoming OWL 2, can accommodate arbitrary Boolean expressions. The prominent OWL-fragment SHIQ can be safely extended by safe role expressions, and the tractable fragments EL++ and DLP retain tractability if extended by conjunction on roles, where in the case of DLP the restriction on role simplicity can even be discarded.

Mobile Semantic Computing, Karthik Gomadam, Anupam Joshi, Amit P. Sheth

Kno.e.sis Publications

We propose to organize a special session on research in the intersection of mobile computing, the Semantic Web and Web services.

This session will examine how the research in these areas can serve as a foundation for new architectural and communication paradigms that can enhance service creation, distribution, discovery, integration and utilization in distributed and ubiquitous environments. Some of the initial areas that our early research have highlighted are :

1. Semantic annotation of data in bandwidth constrained environments such as mobile networks to promote efficient bandwidth utilization
2. Possibilities of using microformats such as RDFa and opportunities that can be explored …

Services Mashups: The New Generation Of Web Applications, Djamal Benslimane, Schahram Dustdar, Amit P. Sheth

Kno.e.sis Publications

Web services are becoming a major technology for deploying automated interactions between distributed and heterogeneous applications, and for connecting business processes. Service mashups indicate a way to create new Web applications by combining existing Web resources utilizing data and Web APIs. They facilitate the design and development of novel and modern Web applications based on easy-to-accomplish end-user service compositions.

On The Tradeoff Between Speedup And Energy Consumption In High Performance Computing – A Bioinformatics Case Study, Sachin Pawaskar, Hesham Ali

Computer Science Faculty Proceedings & Presentations

High Performance Computing has been very useful to researchers in the Bioinformatics, Medical and related fields. The bioinformatics domain is rich in applications that require extracting useful information from very large and continuously growing sequence of databases. Automated techniques such as DNA sequencers, DNA microarrays & others are continually growing the dataset that is stored in large public databases such as GenBank and Protein DataBank. Most methods used for analyzing genetic/protein data have been found to be extremely computationally intensive, providing motivation for the use of powerful computers or systems with high throughput characteristics. In this paper, we provide a …

Semantic Sensor Web, Amit P. Sheth

Kno.e.sis Publications

No abstract provided.

Unsupervised Discovery Of Compound Entities For Relationship Extraction, Cartic Ramakrishnan, Pablo N. Mendes, Shaojun Wang, Amit P. Sheth

Kno.e.sis Publications

In this paper we investigate unsupervised population of a biomedical ontology via information extraction from biomedical literature. Relationships in text seldom connect simple entities. We therefore focus on identifying compound entities rather than mentions of simple entities. We present a method based on rules over grammatical dependency structures for unsupervised segmentation of sentences into compound entities and relationships. We complement the rule-based approach with a statistical component that prunes structures with low information content, thereby reducing false positives in the prediction of compound entities, their constituents and relationships. The extraction is manually evaluated with respect to the UMLS Semantic Network …

Monetizing User Activity On Social Networks, Meenakshi Nagarajan, Kamal Baid, Amit P. Sheth, Shaojun Wang

Kno.e.sis Publications

No abstract provided.

Reasoning In Circumscriptive Alco, Stephan Grimm, Pascal Hitzler

Computer Science and Engineering Faculty Publications

Non-monotonic extensions of description logics (DLs) allow for default and local closed-world reasoning and are an acknowledged desired feature for applications, e.g. in the Semantic Web. A recent approach to such an extension is based on McCarthy's circumscription, which rests on the principle of minimising the extension of selected predicates to locally close off dedicated parts of a domain model. While decidability and complexity results have been established in the literature, no practical algorithmisation for circumscriptive DLs has been proposed so far. In this paper, we present a tableaux calculus that can be used as a sound and complete decision …

Expressive Tractable Description Logics Based On Sroiq Rules, Markus Krotzsch, Sebastian Rudolph, Pascal Hitzler

Computer Science and Engineering Faculty Publications

We introduce description logic (DL) rules as a new rule-based formalism for knowledge representation in DLs. As a fragment of the Semantic Web Rule Language SWRL, DL rules allow for a tight integration with DL knowledge bases. In contrast to SWRL, however, the combination of DL rules with expressive description logics remains decidable, and we show that the DL SROIQ - the basis for the ongoing standardisation of OWL 2 - can completely internalise DL rules. On the other hand, DL rules capture many expressive features of SROIQ that are not available in simpler DLs yet. While reasoning in SROIQ …

Strategic Importance Of Higher Education And Research In Positioning Gujarat For Global Competitiveness, Amit P. Sheth

Kno.e.sis Publications

No abstract provided.

A Coherent Well-Founded Model For Hybrid Mknf Knowledge Bases, Matthias Knorr, Jose Julio Alferes, Pascal Hitzler

Computer Science and Engineering Faculty Publications

With the advent of the Semantic Web, the question becomes important how to best combine open-world based ontology languages, like OWL, with closed-world rules paradigms. One of the most mature proposals for this combination is known as Hybrid MKNF knowledge bases [11], which is based on an adaptation of the stable model semantics to knowledge bases consisting of ontology axioms and rules. In this paper, we propose a well-founded semantics for such knowledge bases which promises to provide better efficiency of reasoning, which is compatible both with the OWL-based semantics and the traditional well-founded semantics for logic programs, and which …

Approximate Owl-Reasoning With Screech, Tuvshintur Tserendorj, Sebastian Rudolph, Markus Krotzsch, Pascal Hitzler

Computer Science and Engineering Faculty Publications

Applications of expressive ontology reasoning for the Semantic Web require scalable algorithms for deducing implicit knowledge from explicitly given knowledge bases. Besides the development of more effi- cient such algorithms, awareness is rising that approximate reasoning solutions will be helpful and needed for certain application domains. In this paper, we present a comprehensive overview of the Screech approach to approximate reasoning with OWL ontologies, which is based on the KAON2 algorithms, facilitating a compilation of OWL DL TBoxes into Datalog, which is tractable in terms of data complexity. We present three different instantiations of the Screech approach, and report on …

Collaborative Ro1 With Ncbo Semantics And Services Enabled Problem Solving Environment For Trypanosoma Cruzi, Amit P. Sheth, Rick Tarleton, Prashant Doshi, Mark Musen, Natasha Noy, Satya S. Sahoo, Daniel B. Weatherly

Kno.e.sis Publications

No abstract provided.

Semantic Sensor Web, Amit P. Sheth, Satya S. Sahoo

Kno.e.sis Publications

Sensors are distributed across the globe leading to an avalanche of data about our environment. It is possible today to utilize networks of sensors to detect and identify a multitude of observations, from simple phenomena to complex events and situations. The lack of integration and communication between these networks, however, often isolates important data streams and intensifies the existing problem of too much data and not enough knowledge. With a view to addressing this problem, the semantic sensor Web (SSW) proposes that sensor data be annotated with semantic metadata that will both increase interoperability and provide contextual information essential for …

Semantic Provenance For Escience: Managing The Deluge Of Scientific Data, Satya S. Sahoo, Amit P. Sheth, Cory Andrew Henson

Kno.e.sis Publications

Provenance information in eScience is metadata that's critical to effectively manage the exponentially increasing volumes of scientific data from industrial-scale experiment protocols. Semantic provenance, based on domain-specific provenance ontologies, lets software applications unambiguously interpret data in the correct context. The semantic provenance framework for eScience data comprises expressive provenance information and domain-specific provenance ontologies and applies this information to data management. The authors' "two degrees of separation" approach advocates the creation of high-quality provenance information using specialized services. In contrast to workflow engines generating provenance information as a core functionality, the specialized provenance services are integrated into a scientific workflow …

Droid: The Drosophila Interactions Database, A Comprehensive Resource For Annotated Gene And Protein Interactions, Jingkai Yu, Svetlana Pacifico, Guozhen Liu, Russell L. Finley Jr

Wayne State University Associated BioMed Central Scholarship

Abstract

Background

Charting the interactions among genes and among their protein products is essential for understanding biological systems. A flood of interaction data is emerging from high throughput technologies, computational approaches, and literature mining methods. Quick and efficient access to this data has become a critical issue for biologists. Several excellent multi-organism databases for gene and protein interactions are available, yet most of these have understandable difficulty maintaining comprehensive information for any one organism. No single database, for example, includes all available interactions, integrated gene expression data, and comprehensive and searchable gene information for the important model organism, Drosophila melanogaster. …

Mcm-Test: A Fuzzy-Set-Theory-Based Approach To Differential Analysis Of Gene Pathways, Lily R. Liang, Vinay Mandal, Yi Lu, Deepak Kumar

Wayne State University Associated BioMed Central Scholarship

Abstract

Background

Gene pathway can be defined as a group of genes that interact with each other to perform some biological processes. Along with the efforts to identify the individual genes that play vital roles in a particular disease, there is a growing interest in identifying the roles of gene pathways in such diseases.

Results

This paper proposes an innovative fuzzy-set-theory-based approach, Multi-dimensional Cluster Misclassification test (MCM-test), to measure the significance of gene pathways in a particular disease. Experiments have been conducted on both synthetic data and real world data. Results on published diabetes gene expression dataset and a list …

Learning Expressive Ontologies, Johanna Volker, Peter Haase, Pascal Hitzler

Computer Science and Engineering Faculty Publications

No abstract provided.

Hrests: An Html Microformat For Describing Restful Web Services, Jacek Kopecky, Karthik Gomadam, Tomas Vitvar

Kno.e.sis Publications

The Web 2.0 wave brings, among other aspects, the Programmable Web: increasing numbers of Web sites provide machine-oriented APIs and Web services. However, most APIs are only described with text in HTML documents. The lack of machine-readable API descriptions affects the feasibility of tool support for developers who use these services. We propose a microformat called hRESTS (HTML for RESTful Services) for machine-readable descriptions of Web APIs, backed by a simple service model. The hRESTS microformat describes main aspects of services, such as operations, inputs and outputs. We also present two extensions of hRESTS: SA-REST, which captures the facets of …

Joint Extraction Of Compound Entities And Relationships From Biomedical Literature, Cartic Ramakrishnan, Pablo N. Mendes, Rodrigo A.T.S. De Gama, Guilherme C.N. Ferreira, Amit P. Sheth

Kno.e.sis Publications

In this paper we identify some limitations of contemporary information extraction mechanisms in the context of biomedical literature. We present an extraction mechanism that generates structured representations of textual content. Our extraction mechanism achieves this by extracting compound entities, and relationships between them, occuring in text. A detailed evaluation of the relationship and compound entities extracted is presented. Our results show over 62% average precision across 8 relationship types tested with over 82% average precision for compound entity identification1.

Targeted Content Delivery For Social Media Content, Meenakshi Nagarajan, Kamal Baid, Amit P. Sheth, Shaojun Wang

Kno.e.sis Publications

Spotting contextually relevant keywords is fundamental to effective content suggestions on the Web. In this regard, misspellings, entity variations and off-topic discussions in content from Social Media pose unique challenges. Here, we present an algorithm that assists content delivery systems by identifying contextually relevant keywords and eliminating off-topic keywords. A preliminary user study over data from MySpace and Facebook clearly suggests the usefulness of our work in delivering more targeted content suggestions.

Traveling The Semantic Web Through Space, Theme And Time, Amit P. Sheth, Matthew Perry

Kno.e.sis Publications

In this installment of Semantics and Services, we further develop the idea of spatial, temporal, and thematic (STT) processing of semantic Web data and describe the Web infrastructure needed to support it. Starting from Ramesh Jain's vision of the EventWeb as a view of what's possible with a Web that better accommodates all three dimensions of event-related information (thematic, spatial, and temporal), we outline the architecture needed to support it and current research that aims to realize it.

Biological Networks: Modeling And Structural Analysis, Emad Y. Ramadan

Computer Science Theses & Dissertations

Biological networks are receiving increased attention due to their importance in understanding life at the cellular level. There exist many different kinds of biological networks, and different models have been proposed for them. In this dissertation we focus on suitable network models for representing experimental data on protein interaction networks and protein complex networks (protein complexes are groups of proteins that associate to accomplish some function in the cell), and to design algorithms for exploring such networks. Our goal is to enable biologists to identify the general principles that govern the organization of protein-protein interaction networks and protein complex networks. …

A General Boosting Method And Its Application To Learning Ranking Functions For Web Search, Zhaohui Zheng, Hongyuan Zha, Tong Zhang, Olivier Chapelle, Keke Chen, Gordon Sun

Kno.e.sis Publications

We present a general boosting method extending functional gradient boosting to optimize complex loss functions that are encountered in many machine learning problems. Our approach is based on optimization of quadratic upper bounds of the loss functions which allows us to present a rigorous convergence analysis of the algorithm. More importantly, this general framework enables us to use a standard regression base learner such as decision trees for fitting any loss function. We illustrate an application of the proposed method in learning ranking functions for Web search by combining both preference data and labeled data for training. We present experimental …

Video On The Semantic Sensor Web, Cory Andrew Henson, Amit P. Sheth, Prateek Jain, Josh Pschorr, Terry Rapoch

Kno.e.sis Publications

Millions of sensors around the globe currently collect avalanches of data about our world. The rapid development and deployment of sensor technology is intensifying the existing problem of too much data and not enough knowledge. With a view to alleviating this glut, we propose that sensor data, especially video sensor data, can be annotated with semantic metadata to provide contextual information about videos on the Web. In particular, we present an approach to annotating video sensor data with spatial, temporal, and thematic semantic metadata. This technique builds on current standardization efforts within the W3C and Open Geospatial Consortium (OGC) and …