no code implementations • 12 Mar 2024 • Ajay Kulkarni, Yingjie Wang, Munisamy Gopinath, Dan Sobien, Abdul Rahman, Feras A. Batarseh
The increasing utilization of emerging technologies in the Food & Agriculture (FA) sector has heightened the need for security to minimize cyber risks.
1 code implementation • 27 Sep 2023 • Feras A. Batarseh, Ajay Kulkarni, Chhayly Sreng, Justice Lin, Siam Maksud
In this paper, the system is introduced in detail and compared with existing water testbeds; additionally, example use-cases are described along with novel outcomes such as datasets, software, and AI-related scenarios.
no code implementations • 21 Jan 2023 • Sai Gurrapu, Ajay Kulkarni, Lifu Huang, Ismini Lourentzou, Laura Freeman, Feras A. Batarseh
Recent improvements in natural language generation have made rationalization an attractive technique because it is intuitive, human-comprehensible, and accessible to non-technical users.
Explainable Artificial Intelligence (XAI) Question Answering +4
1 code implementation • 21 Jan 2023 • Sai Gurrapu, Lifu Huang, Feras A. Batarseh
We introduce a novel claim verification approach, namely: ExClaim, that attempts to provide an explainable claim verification system with foundational evidence.
no code implementations • 27 Dec 2022 • Feras A. Batarseh, Priya L. Donti, Ján Drgoňa, Kristen Fletcher, Pierre-Adrien Hanania, Melissa Hatton, Srinivasan Keshav, Bran Knowles, Raphaela Kotsch, Sean McGinnis, Peetak Mitra, Alex Philp, Jim Spohrer, Frank Stein, Meghna Tare, Svitlana Volkov, Gege Wen
These applications have implications in areas ranging as widely as energy, agriculture, and finance.
no code implementations • 1 Dec 2021 • Andrei Svetovidov, Abdul Rahman, Feras A. Batarseh
Developing and implementing AI-based solutions help state and federal government agencies, research institutions, and commercial companies enhance decision-making processes, automate chain operations, and reduce the consumption of natural and human resources.
no code implementations • 1 Dec 2021 • Md Nazmul Kabir Sikder, Feras A. Batarseh
An outlier is an event or observation that is defined as an unusual activity, intrusion, or a suspicious data point that lies at an irregular distance from a population.
no code implementations • 15 Nov 2021 • Feras A. Batarseh, Munisamy Gopinath, Anderson Monken, Zhengrong Gu
The recent shocks to the free trade regime, especially trade disputes among major economies, as well as black swan events, such as trade wars and pandemics, raise the need for improved predictions to inform policy decisions.
no code implementations • 15 Nov 2021 • Feras A. Batarseh, Laura Freeman
Artificial Intelligence (AI) algorithms are increasingly providing decision making and operational support across multiple domains.
no code implementations • 15 Nov 2021 • Chih-Hao Huang, Feras A. Batarseh, Adel Boueiz, Ajay Kulkarni, Po-Hsuan Su, Jahan Aman
In most cases, such events lead to critical uncertainties in decision making, as well as in multiple medical and economic aspects at a hospital.
no code implementations • 22 Oct 2021 • Sai Gurrapu, Feras A. Batarseh, Pei Wang, Md Nazmul Kabir Sikder, Nitish Gorentala, Gopinath Munisamy
Quantitative metrics that measure the global economy's equilibrium have strong and interdependent relationships with the agricultural supply chain and international trade flows.
no code implementations • 3 Aug 2021 • Feras A. Batarseh, Rasika Mohod, Abhinav Kumar, Justin Bui
This survey chapter is a review of the most commonplace methods of AI applied to SE.
no code implementations • 30 Jul 2021 • Ajay Kulkarni, Deri Chong, Feras A. Batarseh
Dealing with imbalanced data is a prevalent problem while performing classification on the datasets.
no code implementations • 19 Oct 2019 • Feras A. Batarseh, Ajay Kulkarni
Context-driven Data Science Lifecycle (C-DSL); the main contribution of this paper, is developed to address these challenges.