Computer Engineering Commons^™

Mining Sequences Of Developer Interactions In Visual Studio For Usage Smells, Kostadin Damevski, David C. Shepherd, Johannes Schneider, Lori Pollock

Computer Science Publications

In this paper, we present a semi-automatic approach for mining a large-scale dataset of IDE interactions to extract usage smells, i.e., inefficient IDE usage patterns exhibited by developers in the field. The approach outlined in this paper first mines frequent IDE usage patterns, filtered via a set of thresholds and by the authors, that are subsequently supported (or disputed) using a developer survey, in order to form usage smells. In contrast with conventional mining of IDE usage data, our approach identifies time-ordered sequences of developer actions that are exhibited by many developers in the field. This pattern mining workflow is …

An Android-Based Mechanism For Energy Efficient Localization Depending On Indoor/Outdoor Context, Nicholas Capurso, Tianyi Song, Wei Cheng, Jiguo Yu, Xiuzhen Cheng

Computer Science Publications

Today, there is widespread use of mobile applications that take advantage of a user's location. Popular usages of location information include geotagging on social media websites, driver assistance and navigation, and querying nearby locations of interest. However, the average user may not realize the high energy costs of using location services (namely the GPS) or may not make smart decisions regarding when to enable or disable location services-for example, when indoors. As a result, a mechanism that can make these decisions on the user's behalf can significantly improve a smartphone's battery life. In this paper, we present an energy consumption …

Fdetect Webserver: Fast Predictor Of Propensity For Protein Production, Purification, And Crystallization, Fanchi Meng, Chen Wang, Lukasz Kurgan

Computer Science Publications

Background: Development of predictors of propensity of protein sequences for successful crystallization has been actively pursued for over a decade. A few novel methods that expanded the scope of these predictions to address additional steps of protein production and structure determination pipelines were released in recent years. The predictive performance of the current methods is modest. This is because the only input that they use is the protein sequence and since the experimental annotations of these data might be inconsistent given that they were collected across many laboratories and centers. However, even these modest levels of predictive quality are still …

Parsing Metamap Files In Hadoop, Amy Olex, Alberto Cano, Bridget T. Mcinnes

Computer Science Publications

The UMLS::Association CUICollector module identifies UMLS Concept Unique Identifier bigrams and their frequencies in a biomedical text corpus. CUICollector was re-implemented in Hadoop MapReduce to improve algorithm speed, flexibility, and scalability. Evaluation of the Hadoop implementation compared to the serial module produced equivalent results and achieved a 28x speedup on a single-node Hadoop system.

Sotxtstream: Density-Based Self-Organizing Clustering Of Text Streams, Avory C. Bryant, Krzysztof J. Cios

Computer Science Publications

A streaming data clustering algorithm is presented building upon the density-based selforganizing stream clustering algorithm SOSTREAM. Many density-based clustering algorithms are limited by their inability to identify clusters with heterogeneous density. SOSTREAM addresses this limitation through the use of local (nearest neighbor-based) density determinations. Additionally, many stream clustering algorithms use a two-phase clustering approach. In the first phase, a micro-clustering solution is maintained online, while in the second phase, the micro-clustering solution is clustered offline to produce a macro solution. By performing self-organization techniques on micro-clusters in the online phase, SOSTREAM is able to maintain a macro clustering solution in …

Ensemble Learning For Data Stream Analysis: A Survey, Bartosz Krawczyk, Leandro L. Minku, João Gama, Jerzy Stefanowski, Michał Wozniak

Computer Science Publications

In many applications of information systems learning algorithms have to act in dynamic environments where data are collected in the form of transient data streams. Compared to static data mining, processing streams imposes new computational requirements for algorithms to incrementally process incoming examples while using limited memory and time. Furthermore, due to the non-stationary characteristics of streaming data, prediction models are often also required to adapt to concept drifts. Out of several new proposed stream algorithms, ensembles play an important role, in particular for non-stationary environments. This paper surveys research on ensembles for data stream classification as well as regression …

Quadmutex: Quadratic Driver Mutation Explorer, Bokhari Yahya, Tomasz Jakub Arodz

Computer Science Publications

Background

Somatic mutations accumulate in human cells throughout life. Some may have no adverse consequences, but some of them may lead to cancer. A cancer genome is typically unstable, and thus more mutations can accumulate in the DNA of cancer cells. An ongoing problem is to figure out which mutations are drivers - play a role in oncogenesis, and which are passengers - do not play a role. One way of addressing this question is through inspection of somatic mutations in DNA of cancer samples from a cohort of patients and detection of patterns that differentiate driver from passenger mutations. …

An Integrative In-Silico Approach For Therapeutic Target Identification In The Human Pathogen Corynebacterium Diphtheriae, Syed Babar Jamal, Syed Shah Hassan, Sandeep Tiwari, Marcus V. Viana, Leandro De Jesus Benevides, Asad Ullah, Adrián G. Turjanski, Debmalya Barh, Preetam Ghosh, Daniela Arruda Costa, Artur Silva, Richard Röttger, Jan Baumbach, Vasco A.C. Azevedo

Computer Science Publications

Corynebacterium diphtheriae (Cd) is a Gram-positive human pathogen responsible for diphtheria infection and once regarded for high mortalities worldwide. The fatality gradually decreased with improved living standards and further alleviated when many immunization programs were introduced. However, numerous drug-resistant strains emerged recently that consequently decreased the efficacy of current therapeutics and vaccines, thereby obliging the scientific community to start investigating new therapeutic targets in pathogenic microorganisms. In this study, our contributions include the prediction of modelome of 13 C. diphtheriae strains, using the MHOLline workflow. A set of 463 conserved proteins were identified by combining the results of pangenomics …

Crosstalk And The Dynamical Modularity Of Feed-Forward Loops In Transcriptional Regulatory Networks, Michael A. Rowland, Ahmed Abdelzaher, Preetam Ghosh, Michael L. Mayo

Computer Science Publications

Network motifs, such as the feed-forward loop (FFL), introduce a range of complex behaviors to transcriptional regulatory networks, yet such properties are typically determined from their isolated study. We characterize the effects of crosstalk on FFL dynamics by modeling the cross regulation between two different FFLs and evaluate the extent to which these patterns occur in vivo. Analytical modeling suggests that crosstalk should overwhelmingly affect individual protein-expression dynamics. Counter to this expectation we find that entire FFLs are more likely than expected to resist the effects of crosstalk (approximate to 20% for one crosstalk interaction) and remain dynamically modular. The …