Browsing by Author "Shahin, Hossameldin L."

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    Classification Project in CS5604, Spring 2016
    Bock, Matthew; Cantrell, Michael; Shahin, Hossameldin L. (2016-05-04)
    In the grand scheme of a large Information Retrieval project, the work of our team was that of performing text classification on both tweet collections and their associated webpages. In order to accomplish this task, we sought to complete three primary goals. We began by performing research to determine the best way to extract information that can be used to represent a given document. Following that, we worked to determine the best method to select features and then construct feature vectors. Our final goal was to use the information gathered previously to build an effective way to classify each document in the tweet and webpage collections. These classifiers were built with consideration of the ontology developed for the IDEAL project. To truly show the effectiveness of our work at accomplishing our intended goals, we also provide an evaluation of our methodologies. The team assigned to perform this classification work last year researched various methods and tools that could be useful in accomplishing the goals we have set forth. Last year’s team developed a system that was able to accomplish similar goals to those we have set forth with a promising degree of success. Our goal for this year was to improve upon their successes using new technologies such as Apache Spark. Spark has provided us with the tools needed to build a well optimized system capable of working with the provided small collections of tweets and webpages in a fast and efficient manner. Spark is also very scalable, and based on our results with the small collections we have confidence in the performance of our system on larger collections. Also included in this submission is our final presentation of the project as presented to the CS5604 class, professor, and GRAs. The presentation provides a high level overview of the project requirements and our approach to them, as well as details about our implementation and evaluation. The submission also includes our source code, so that future classes can expand on the work we have done this semester.
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    Design and Implementation of OpenDSA Interoperable Infrastructure
    Shahin, Hossameldin L. (Virginia Tech, 2017-08-09)
    OpenDSA is a system for creating rich eTextbooks that combine quality text with visualizations and interactive, auto-graded exercises. As OpenDSA gains recognition, its use increases each year. This mandates a scalable, reliable, and sustainable infrastructure to accommodate the fast-growing demand for OpenDSA access. We implemented OpenDSA-LTI, an interoperable infrastructure which transforms OpenDSA from a standalone, self-contained eTextbook to an integrated learning tool communicating with a Learning Management System (LMS) through the Learning Tool Interoperability (LTI) protocol. OpenDSA-LTI delivers OpenDSA content and interactive materials to students through a reliable and secure LMS interface. LTI integration encourages OpenDSA adoption by providing easy, intuitive tools that help instructors to build and generate OpenDSA eTextbooks in their LMS courses. OpenDSA-LTI allows OpenDSA content developers to take advantage of various tools already provided by the LMS instead of reproducing these through their own proprietary services. The OpenDSA-LTI extendable design allows for adding new LTI-compliant exercises to OpenDSA books. This changes OpenDSA developers' efforts to searching for learning tools instead of reimplementing them. As an example, instead of maintaining the original OpenDSA programming evaluation engine, we could easily replace it with the Code Workout online drill-and-practice system. Since its launch in August 2016 until June 2017, OpenDSA-LTI has hosted 36 active courses offered by 25 different universities in 6 countries, 41 instructors have used OpenDSA-LTI to host their courses on the Canvas LMS, and the system has 2,729 registered students.
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    PlantSimLab - a modeling and simulation web tool for plant biologists
    Ha, Sook; Dimitrova, ‪Elena; Hoops, Stefan; Altarawy, Doaa; Ansariola, Mitra; Deb, Devdutta; Glazebrook, Jane; Hillmer, Rachel; Shahin, Hossameldin L.; Katagiri, Fumiaki; McDowell, John M.; Megraw, Molly; Setubal, João C.; Tyler, Brett M.; Laubenbacher, Reinhard C. (2019-10-21)
    Background At the molecular level, nonlinear networks of heterogeneous molecules control many biological processes, so that systems biology provides a valuable approach in this field, building on the integration of experimental biology with mathematical modeling. One of the biggest challenges to making this integration a reality is that many life scientists do not possess the mathematical expertise needed to build and manipulate mathematical models well enough to use them as tools for hypothesis generation. Available modeling software packages often assume some modeling expertise. There is a need for software tools that are easy to use and intuitive for experimentalists. Results This paper introduces PlantSimLab, a web-based application developed to allow plant biologists to construct dynamic mathematical models of molecular networks, interrogate them in a manner similar to what is done in the laboratory, and use them as a tool for biological hypothesis generation. It is designed to be used by experimentalists, without direct assistance from mathematical modelers. Conclusions Mathematical modeling techniques are a useful tool for analyzing complex biological systems, and there is a need for accessible, efficient analysis tools within the biological community. PlantSimLab enables users to build, validate, and use intuitive qualitative dynamic computer models, with a graphical user interface that does not require mathematical modeling expertise. It makes analysis of complex models accessible to a larger community, as it is platform-independent and does not require extensive mathematical expertise.