• Working Group Recommendations for an Indiana University Research Data Commons 

  Simon, Kosali; Dallis-Comentale, Diane; Fang, Shiaofen; Huang, Kun; Link, Matt; Maupome, Gerardo; Menczer, Filippo; Neal, Aaron; Perry, Brea; Plale, Beth; Raymond, Angie; Wiehe, Sarah (2022-06-30)

  Starting on April 28, 2022, our Working Group set out to make recommendations for an Indiana University Research Data Commons (IU-RDCom), a strategy to identify and meet the growing needs associated with research data at ...
• ASPER: Attention-based Approach to Extract Syntactic Patterns denoting Semantic Relations in Sentential Context 

  Md. Ahsanul, Kabir; Typer, Philips; Xiao, Luo; Mohammed, Al Hasan (2021)

  Semantic relationships, such as hyponym-hypernym, cause-effect, meronym-holonym etc., between a pair of entities in a sentence are usually reflected through syntactic patterns. Automatic extraction of such patterns benefits ...
• Energy-Efficient Device Selection in Federated Edge Learning 

  Peng, Cheng; Hu, Qin; Chen, Jianan; Kang, Kyubyung; Li, Feng; Zou, Xukai (IEEE, 2021-07)

  Due to the increasing demand from mobile devices for the real-time response of cloud computing services, federated edge learning (FEL) emerges as a new computing paradigm, which utilizes edge devices to achieve efficient ...
• Privacy-Aware Data Trading 

  Wang, Shengling; Shi, Lina; Hu, Qin; Zhang, Junshan; Cheng, Xiuzhen; Yu, Jiguo (IEEE Xplore, 2021-07)

  The growing threat of personal data breach in data trading pinpoints an urgent need to develop countermeasures for preserving individual privacy. The state-of-the-art work either endows the data collector with the ...
• Hippocampal Subregion and Gene Detection in Alzheimer’s Disease Based on Genetic Clustering Random Forest 

  Li, Jin; Liu, Wenjie; Cao, Luolong; Luo, Haoran; Xu, Siwen; Bao, Peihua; Meng, Xianglian; Liang, Hong; Fang, Shiaofen (MDPI, 2021-05-01)

  The distinguishable subregions that compose the hippocampus are differently involved in functions associated with Alzheimer's disease (AD). Thus, the identification of hippocampal subregions and genes that classify AD and ...
• Advances in Mobile Communications and Computing 

  Durresi, Arjan; Denko, Mieso (Hindawi, 2009)
• COVID CV: A System for Creating Holistic Academic CVs during a Global Pandemic 

  Raja, Umesh; Chowdhury, Nahida Sultana; Raje, Rajeev R.; Wheeler, Rachel; Williams, Jane; Ganci, Aaron (IEEE, 2021-05)

  The effects of the Covid pandemic have been, similar to the population at-large, unequal on academicians - some groups have been more susceptible than others. Traditional CVs are inadequate to highlight these imbalances. ...
• Genome-wide variant-based study of genetic effects with the largest neuroanatomic coverage 

  Li, Jin; Liu, Wenjie; Li, Huang; Chen, Feng; Luo, Haoran; Bao, Peihua; Li, Yanzhao; Jiang, Hailong; Gao, Yue; Liang, Hong; Fang, Shiaofen (BMC, 2021-04-30)

  Background: Brain image genetics provides enormous opportunities for examining the effects of genetic variations on the brain. Many studies have shown that the structure, function, and abnormality (e.g., those related to ...
• A modified two-process Knox test for investigating the relationship between law enforcement opioid seizures and overdoses 

  Mohler, G.; Mishra, S.; Ray, B.; Magee, L.; Huynh, P.; Canada, M.; O’Donnell, D.; Flaxman, S. (The Royal Society, 2021-06)

  Recent research has shown an association between monthly law enforcement drug seizure events and accidental drug overdose deaths using cross-sectional data in a single state, whereby increased seizures correlated with more ...
• RASMA: a reverse search algorithm for mining maximal frequent subgraphs 

  Salem, Saeed; Alokshiya, Mohammed; Hasan, Mohammad Al (BMC, 2021-03-16)

  Background: Given a collection of coexpression networks over a set of genes, identifying subnetworks that appear frequently is an important research problem known as mining frequent subgraphs. Maximal frequent subgraphs ...
• Learning network event sequences using long short-term memory and second-order statistic loss 

  Sha, Hao; Al Hasan, Mohammad; Mohler, George (Wiley, 2021-02)

  Modeling temporal event sequences on the vertices of a network is an important problem with widespread applications; examples include modeling influences in social networks, preventing crimes by modeling their space–time ...
• Deep Intact Proteoform Characterization in Human Cell Lysate using High-pH and Low-pH Reversed-Phase Liquid Chromatography 

  Yu, Dahang; Wang, Zhe; Sutton, Kellye A.; Liu, Xiaowen; Wu, Si (American Chemical Society, 2019-12)

  Post-translational modifications (PTMs) play critical roles in biological processes and have significant effects on the structures and dynamics of proteins. Top-down proteomics methods were developed for and applied to the ...
• Learning to rank spatio-temporal event hotspots 

  Mohler, George; Porter, Michael; Carter, Jeremy; LaFree, Gary (BMC, 2020)

  Background Crime, traffic accidents, terrorist attacks, and other space-time random events are unevenly distributed in space and time. In the case of crime, hotspot and other proactive policing programs aim to focus limited ...
• Rainbows Revisited: Modeling Effective Colormap Design for Graphical Inference 

  Reda, Khairi; Albers Szafir, Danielle (IEEE, 2020-10)

  Color mapping is a foundational technique for visualizing scalar data. Prior literature offers guidelines for effective colormap design, such as emphasizing luminance variation while limiting changes in hue. However, ...
• Reliability Maximization in Uncertain Graphs 

  Ke, Xiangyu; Khan, Arijit; Al Hasan, Mohammad; Rezvansangsari, Rojin (IEEE, 2020-04)

  Network reliability measures the probability that a target node is reachable from a source node in an uncertain graph, i.e., a graph where every edge is associated with a probability of existence. In this paper, we investigate ...
• ElasticBroker: Combining HPC with Cloud to Provide Realtime Insights into Simulations 

  Li, Feng; Wang, Dali; Yan, Feng; Song, Fengguang (arXiv, 2020)

  For large-scale scientific simulations, it is expensive to store raw simulation results to perform post-analysis. To minimize expensive I/O, "in-situ" analysis is often used, where analysis applications are tightly coupled ...
• Coupled IGMM-GANs with Applications to Anomaly Detection in Human Mobility Data 

  Smolyak, Daniel; Gray, Kathryn; Badirli, Sarkhan; Mohler, George (ACM, 2020-12)

  Detecting anomalous activity in human mobility data has a number of applications, including road hazard sensing, telematics-based insurance, and fraud detection in taxi services and ride sharing. In this article, we address ...
• Control Theoretical Modeling of Trust-Based Decision Making in Food-Energy-Water Management 

  Uslu, Suleyman; Kaur, Davinder; Rivera, Samuel J.; Durresi, Arjan; Babbar-Sebens, Meghna; Tilt, Jenna H. (Springer, 2021)

  We propose a hybrid Human-Machine decision making to manage Food-Energy-Water resources. In our system trust among human actors during decision making is measured and managed. Furthermore, such trust is used to pressure ...
• Quantum Analysis on Task Allocation and Quality Control for Crowdsourcing With Homogeneous Workers 

  Xu, Minghui; Wang, Shengling; Hu, Qin; Sheng, Hao; Cheng, Xiuzhen (IEEE, 2020-05)

  Crowdsourcing has been emerging as a valid problem-solving model that harnesses a large group of contributors to solve a complicated task. However, existing crowdsourcing platforms or systems could suffer from task allocation ...
• Requirements for Trustworthy Artificial Intelligence – A Review 

  Kaur, Davinder; Uslu, Suleyman; Durresi, Arjan (Springer, 2021)

  The field of algorithmic decision-making, particularly Artificial Intelligence (AI), has been drastically changing. With the availability of a massive amount of data and an increase in the processing power, AI systems have ...

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