Towards Improving Interface Modularity in Legacy Java Software Through Automated Refactoring

N928 300 Jay St., Room N928, Brooklyn, NY

The skeletal implementation pattern is a software design pattern consisting of defining an abstract class that provides a partial interface implementation. However, since Java allows only single class inheritance, if implementers decide to extend a skeletal implementation, they will not be allowed to extend any … Continue reading

Bio-inspired Computation Approach for Tumor Growth with Spatial Randomness Analysis of Kidney Cancer Xenograft Pathology Slides

N928 300 Jay St., Room N928, Brooklyn, NY

In our research, we analyze digitized images of Hematoxylin-Eosin (H&E) slides equipped with tumorous tissues from patient derived xenograft models to build our bio-inspired computation method, namely Personalized Relevance Parameterization of Spatial Randomness (PReP-SR). Applying spatial pattern analysis techniques of quadrat counts, kernel estimation and nearest neighbor functions to the images of the H&E samples, slide-specific features are extracted to examine the hypothesis that existence of dependency of nuclei positions possesses information of individual tumor characteristics. These features are then used as inputs to PReP-SR to compute tumor growth parameters for exponential-linear model. Differential evolution algorithms are developed for tumor growth parameter computations, where a candidate vector in a population consists of size selection indices for spatial evaluation and weight coefficients for spatial features and their correlations. Using leave-one-out-cross-validation method, we showed that, for a set of H&E slides from kidney cancer patient derived xenograft models, PReP-SR generates personalized model parameters with an average error rate of 13:58%. The promising results indicate that bio-inspired computation techniques may be useful to construct mathematical models with patient specific growth parameters in clinical systems.

NYC, Media and Technology: What’s Hot

N928 300 Jay St., Room N928, Brooklyn, NY

Founded in 2010, NYC Media Lab is dedicated to driving innovation and ultimately job growth in media and technology by facilitating collaboration between the City’s universities and its companies. Comprised of a consortium including New York City Economic Development Corporation, New York University, Columbia University, The New School, CUNY, and Pratt Institute, NYC Media Lab's goals include generating research and development, knowledge transfer, and talent development across all of the City’s campuses. Justin will describe NYC Media Lab, its projects, and the curiosities of its member companies.

Ontology-based Classification and Faceted Search Interface for APIs

N928 300 Jay St., Room N928, Brooklyn, NY

This work introduces faceted service discovery. It uses the Programmable Web directory as its corpus of APIs and enhances the search to enable faceted search, given an OWL ontology. The ontology describes semantic features of the APIs. We have designed the API classification ontology using LexOnt, a software we have built for semi-automatic ontology creation tool. LexOnt is geared toward non-experts within a service domain who want to create a high-level ontology that describes the domain. Using well- known NLP algorithms, LexOnt generates a list of top terms and phrases from the Programmable Web corpus to enable users to find high-level features that distinguish one Programmable Web service category from another. To also aid non-experts, LexOnt relies on outside sources such as Wikipedia and Wordnet to help the user identify the important terms within a service category. Using the ontology created from LexOnt, we have created APIBrowse, a faceted search interface for APIs. The ontology, in combination with the use of the Apache Solr search platform, is used to generate a faceted search interface for APIs based on their distinguishing features. With this ontology, an API is classified and displayed underneath multiple categories and displayed within the APIBrowse interface. APIBrowse gives programmers the ability to search for APIs based on their semantic features and keywords and presents them with a filtered and more accurate set of search results.

Energy Management as a Service (EMaaS)

N907 300 Jay Street, Brooklyn, NY

Yu-Wen Chen, PhD Assistant Professor, CST Dept. December 7, 12pm-1pm, Room N907 Dr. Chen presents an introduction to smart grid and cloud computing as the foundation for the design of customer-oriented energy-efficient systems (EmaaS). These systems provide financial incentives to … Continue reading

Applied AI Techniques


Will Ross Business Development, M& A IBM Watson Group     In a world of open data and consumer platforms it is easy to forget the significant quantities of high-value data still held by entities who view or require those … Continue reading

Eager Execution in TensorFlow


Alexandre Passos Software Engineer, Google             In this talk we'll go over TensorFlow, an open- source cross-platform machine learning library developed by Google, and explore its new feature: eager execution. We'll go over how to … Continue reading

Sports Data Science


Claudio T. Silva Professor, Computer Science  & Engineering. New York University November 14, 2019 12pm-1pm Room N918   New technology is starting to enable the capture of game play at unprecedented levels of detail, including the tracking of positions of … Continue reading