Engineering Commons^™

Architecture Of Heptagonal Metallo-Macrocycles Via Embedding Metal Nodes Into Its Rigid Backbone, A.M.Shashika D. Wijerathna, He Zhao, Qiangqiang Dong, Qixia Bai, Zhiyuan Jiang, Jie Yuan, Jun Wang, Mingzhao Chen, Markus Zirnheld, Rockwell T. Li, Yuan Zhang, Yiming Li, Pingshan Wang

College of Sciences Posters

Metal-organic macrocycles have received increasing attention not only due to their versatile applications such as molecular recognition, compounds encapsulation, anti-bacteria and others, but also for their important role in the study of structure-property relationship at nano scale. However, most of the constructions utilize benzene ring as the backbone, which restricts the ligand arm angle in the range of 60, 120 and 180 degrees. Thus, the topologies of most metallo-macrocycles are limited as triangles and hexagons, and explorations of using other backbones with large angles and the construction of metallo-macrocycles with more than six edges are very rare.

In this study, …

The Message Design Of Raiders Of The Lost Ark On The Atari 2600 & A Fan’S Map, Quick Start, And Strategy Guide, Miguel Ramlatchan, William I. Ramlatchan

Distance Learning Faculty & Staff Books

The message design and human performance technology in video games, especially early video games have always been fascinating to me. From an instructional design perspective, the capabilities of the technology of the classic game consoles required a careful balance of achievable objectives, cognitive task analysis, guided problem solving, and message design. Raiders on the Atari is an excellent example of this balance. It is an epic adventure game, spanning 13+ distinct areas, with an inventory of items, where those hard to find items had to be used by the player to solve problems during their quest (and who would have …

Analysis Of An Existing Method In Refinement Of Protein Structure Predictions Using Cryo-Em Images, Maytha Alshammari, Jing He, Willy Wriggers, Jiangwen Sun

College of Sciences Posters

Protein structure prediction produces atomic models from its amino acid sequence. Three-dimensional structures are important for understanding the function mechanism of proteins. Knowing the structure of a given protein is crucial in drug development design of novel enzymes. AlphaFold2 is a protein structure prediction tool with good performance in recent CASP competitions. Phenix is a tool for determination of a protein structure from a high-resolution 3D molecular image. Recent development of Phenix shows that it is capable to refine predicted models from AlphaFold2, specifically the poorly predicted regions, by incorporating information from the 3D image of the protein. The goal …

Human Interaction With Fake News, Autumn Woodson, Sampath Jayarathna (Mentor)

Computer & Information Science: Research Experiences for Undergraduates in Disinformation Detection and Analytics

No abstract provided.

Data-Limited Domain Adaptation And Transfer Learning For Learning Latent Expression Labels Of Child Facial Expression Images, Megan Witherow, Winston Shields, Manar Samad, Khan Iftekharuddin

College of Engineering & Technology (Batten) Posters

While state-of-the-art deep learning models have demonstrated success in adult facial expression classification by leveraging large, labeled datasets, labeled data for child facial expression classification is limited. Due to differences in facial morphology and development in child and adult faces, deep learning models trained on adult data do not generalize well to child data. Recent deep domain adaptation approaches have improved the generalizability of models trained on a source domain to a target domain with few labeled samples. We propose that incorporating steps of deep transfer learning, e.g. weights initialization from the pre-trained source model and freezing model layers, may …

Unsupervised Multivariate Time Series Clustering, Md Monibor Rahman, Lasitha Vidyaratne, Alex Glandon, Khan Iftekharuddin

College of Engineering & Technology (Batten) Posters

Clustering is widely used in unsupervised machine learning to partition a given set of data into non-overlapping groups. Many real-world applications require processing more complex multivariate time series data characterized by more than one dependent variables. A few works in literature reported multivariate classification using Shapelet learning. However, the clustering of multivariate time series signals using Shapelet learning has not explored yet. Shapelet learning is a process of discovering those Shapelets which contain the most informative features of the time series signal. Discovering suitable Shapelets from many candidates Shapelet has been broadly studied for classification and clustering of univariate time …

Nanopore Guided Regional Assembly, Eleni Adam, Desh Ranjan, Harold Riethman

College of Sciences Posters

The telomeres are the “caps” of the chromosomes and their vital role is to protect them. Possible telomere dysfunction caused by telomere rearrangements can be fatal for the cell and result in age-related diseases, including cancer. The telomeres and subtelomeres are regions that are hard to investigate. The current technology cannot provide their complete sequence, instead the DNA is given in multiple pieces. Current methods of assembling the pieces of these regions are not accurate enough due to the region’s high variability and complex repeated patterns. We propose a hybrid assembly method, the NPGREAT, which utilizes two of the latest …

Strategies For Sensor Data Aggregation In Support Of Emergency Response, X. Wang, A. Walden, M. Weigle, S. Olariu

Computer Science Presentations

PDF of a powerpoint presentation from the Military Communications Conference (MILCOM), Baltimore, Maryland, October 7, 2014. Also available on Slideshare.

Communications And Energy-Harvesting In Nanosensor Networks, Michele C. Weigle

Computer Science Presentations

PDF of a powerpoint presentation from the National Science Foundation (NSF) Workshop on Biological Computations and Communications in Boston, Massachusetts, November 9, 2012. Also available on Slideshare.

Climate Change And Sea Level Rise Initiative (Ccslri), Larry P. Atkinson

CCSLRI Brochures

Brochure of the Old Dominion University Climate Change and Sea Level Rise Initiative (CCSLRI)

Using Timed-Release Cryptography To Mitigate The Preservation Risk Of Embargo Periods, Rabia Haq, Michael L. Nelson

Computer Science Presentations

PDF of a powerpoint presentation from the 2009 ACM/IEEE Joint Conference on Digital Libraries, Austin, Texas, June 15-19, 2009. Also available on Slideshare.