Ricky J Sethi

Fitchburg State University · Computer Science Department

The proliferation of fake news in today’s digital world has moved beyond a specific election cycle and now com- mands headlines globally. In this paper, we propose countering the spread of fake news on social networks by leveraging these crowds to instead help verify alternative facts. We present a prototype social argumentation framework to verify...

We have created an open access online platform for using semantic workflows to analyze artistic style in paintings. We have implemented workflows for both standard computer vision image processing techniques and state-of-the-art methods such as convolutional neural networks to analyze images. These workflows can be used online by non-experts withou...

Why a book on CS0 from scratch? Most of us write the books that we would have wanted to read and this is no different. As such, it follows a normal CS0 breadth-first approach but lays particular emphasis on computational thinking and related topics in data science. My hope is this book will help build a theoretical and practical foundation for l...

Dealing with complex and controversial topics like the spread of misinformation is a salient aspect of our lives. In this paper, we present initial work towards developing a recommendation system that uses crowd-sourced social argumentation with pedagogical agents to help combat misinformation. We model users’ emotional associations on such topics...

This foundational research provides additional support for using the Fuzzy ARTMAP neural network as a classification algorithm in the TAR domain. While research opportunities exist to improve recall performance and explanation, the robust recall results from this study and the proof-of-concept demonstration of If-Then rules for tf-idf vectorization...

In this paper, we present initial work towards creating an intelligent interface that can act as an open access laboratory for visual stylometry called WAIVS, Workflows for Analysis of Images and Visual Stylometry. WAIVS allows scholars, students, and other interested parties to explore the nature of artistic style using cutting-edge research metho...

Using Intelligent Workflows to Analyze Artistic Style USC Information Sciences Institute (ISI) alumnus Ricky J. Sethi and his colleagues at Fitchburg State University in Massachusetts are using ISI's WINGS workflow system for art history in the WAIVS (Workflows for Analysis of Images and Visual Stylometry) project. WAIVS workflows were demonstrated...

Fake news and alternative facts have dominated the news cycle of late. In this paper, we present a prototype system that uses social argumentation to verify the validity of proposed alternative facts and help in the detection of fake news. We utilize fundamental argumentation ideas in a graph-theoretic framework that also incorporates semantic web...

We have recently developed a prototype using a social argumentation framework to allow virtual communities to check alternative facts. We use a graph-theoretic representation of an argument and also utilize semantic web and linked data principles in creating an argumentation graph. The creation of the argumentation graph is crowdsourced and mediate...

The Park City Math Institute 2016 Summer Undergraduate Faculty Program met for the purpose of composing guidelines for undergraduate programs in data science. The group consisted of 25 undergraduate faculty from a variety of institutions in the United States, primarily from the disciplines of mathematics, statistics, and computer science. These gui...

In this paper, we demonstrate the use of scientific workflows in bridging expertise across multiple domains by re-purposing workflow fragments in the areas of text analysis, image analysis, and analysis of activity in video. We highlight how the reuse of workflows allows scientists to link across disciplines and avail themselves of the benefits of...

Artistic style plays a critical role in our commerce with artworks. Artworks are artifacts that mediate a complex communicative exchange between artists and consumers, or more broadly among members of an artistic community. Artistic style is a perceptible quality of the appearance of an artwork that enables us to recognize it as belonging to one ca...

Collaboration, extension, and reproduction of research is of great importance in computer vision. Scientific workflows offer a unique framework for distributed collaboration and sharing of experiments. They provide a structured, end-to-end analysis methodology that easily and automatically allows for standardized replication and testing of models,...

Reproducibility of research is an area of growing concern in computer vision. Scientific workflows provide a structured methodology for standardized replication and testing of state-of-the-art models, open publication of datasets and software together, and ease of analysis by re-using pre-existing components. In this paper, we present initial work...

Biomedical literature incorporates millions of figures, which are a rich and important knowledge resource for biomedical researchers. Scientists need access to the figures and the knowledge they represent in order to validate research findings and to generate new hypotheses. By themselves, these figures are nearly always incomprehensible to both hu...

The neurobiological model for motion recognition and visual processing posits that visual stimuli in the brain bifurcate into a Motion Energy Pathway and a Form Pathway, both of which are finally Integrated in the resulting motion recognition. In this article, we propose a perceptually-inspired computational framework for video search and analysis...

Analyzing web content, particularly multimedia content, for security applications is of great interest. However, it often requires deep expertise in data analytics that is not always accessible to non-experts. Our approach is to use scientific work ows that capture expert-level methods to examine web content. We use work ows to analyze the image an...

Motion and image analysis are both important for robust solutions to video search of activities; the physics-based, data-driven Hamiltonian Monte Carlo (HMC), a Markov chain Monte Carlo variant that is efficient in searching large dimensional spaces, simultaneously examines the combined motion and image space. In this paper, we generalize the data-...

Semantic wikis augment wikis with semantic properties that can be used to aggregate and query data through reasoning. Semantic wikis are used by many communities, for widely varying purposes such as organizing genomic knowledge, coding software, and tracking environmental data. Although wikis have been analyzed extensively, there has been no publis...

Semantic wikis augment wikis with semantic properties that can be used to aggregate and query data through reasoning. Semantic wikis are used by many communities, for widely varying purposes such as organizing genomic knowledge, coding software, and tracking environmental data. Although wikis have been analyzed extensively, there has been no publis...

Crowd analysis is a popular topic in computer vision, with important applications to video surveillance, social media analysis, and multimedia retrieval, to name just a few areas. In this paper, we review some of the physics-based methods for group and crowd analysis in computer vision. In particular, we examine approaches for physics-based analysi...

Internet-based volunteer communities collaboratively contribute to the expansion of human knowledge and cognition. Their popularity is evidenced not only by reference sites like Wikipedia but also by niche communities designed to help people answer complex queries, especially in relation to highly technical or scientific subjects that are beyond th...

In this paper, we demonstrate the ability to reuse workflow fragments in different data domains: from text analytics to image analysis to video activity recognition. We highlight how the re-use of workflows allows scientists to link across disciplines and avail themselves of the benefits of interdisciplinary research beyond their normal area of exp...

In this paper, we present a set of measures to quantify certain properties of threaded discussions, which are ubiquitous in online learn-ing platforms. In particular, we address how to measure the redundancy of posts, the compactness of topics, and the degree of hierarchy in sub-threads. This preliminary work would very much benefit from discussion...

In this paper, we present a set of measures to quantify certain properties of threaded discussions, which are ubiquitous in online learning platforms. In particular, we address how to measure the redundancy of posts, the compactness of topics, and the degree of hierarchy in sub-threads. This preliminary work would very much benefit from discussion...

The demand for advanced skills in data analysis spans many areas of science, computing, and business analytics. This paper discusses how non-expert users reuse workflows created by experts and representing complex data mining processes for text analytics. They include workflows for document classification, document clustering, and topic detection,...

This paper concentrates on the problem of modelling and recognition of complex behaviours involving multi-object interactions in video. We use motion patterns of individual objects to construct models which characterize pairs by correlating them in phase space. These models of complex interactions allow for: recognition of group activities, which o...

Introduction Interpreting how people walk is intuitive for humans. From birth, we observe physical motion in the world around us and create perceptual models to make sense of it. Neurobiologically, we invent a framework within which we understand and interpret human activities like walking (Kandel et al. 2000). Analogously, in this chapter we propo...

In this paper, we propose an innovative approach for the development of social collaboration argumentation systems. These systems enable a community to collaboratively create answers to questions where many possible answers, or nuanced perspectives on a single answer, can be posited. We examine the emergence of critical reasoning via crowdsourced s...

Maintaining the stability of tracks on multiple targets in video over extended time periods and wide areas remains a challenging problem. Basic trackers like the Kalman filter or particle filter deteriorate in performance as the complexity of the scene increases. A few methods have recently shown encouraging results in these application domains. Th...

Activity recognition is a field of computer vision which has shown great progress in the past decade. Starting from simple single person activities, research in activity recognition is moving toward more complex scenes involving multiple objects and natural environments. The main challenges in the task include being able to localize and recognize e...

Maintaining the stability of tracks on multiple targets in video over ex-tended time periods and wide areas remains a challenging problem. Basic trackers like the Kalman filter or particle filter deteriorate in performance as the complexity of the scene increases. A few methods have recently shown encouraging results in these application domains. T...

The Neurobiological model of motion recognition posits a Motion Energy Pathway and a Form Pathway but leaves the mechanism for Integration open. In this paper, we present a stochastic Integration methodology, based on the Hamiltonian Monte Carlo, which explores both the Motion and Form space by creating data-driven proposals in the image/form space...

Recognizing a person's motion is intuitive for hu- mans but represents a challenging problem in machine vision. In this paper, we present a multi-disciplinary framework for recognizing human actions. We develop a novel descriptor, the Human Action Image (HAI): a physically-significant, compact representation for the motion of a person, which we der...

Recognizing a person's motion is intuitive for humans but represents a challenging problem in machine vision. In this paper, we present a multi-disciplinary framework for recognizing human actions. We develop a novel descriptor, the Human Action Image (HAI), a physically-significant, compact representation for the motion of a person, which we deriv...

In this paper, we employ ideas grounded in physics to examine activities in video. We build the Multi-Resolution Phase Space (MRPS) descriptor, which is a set of feature descriptors that is able to represent complex activities in multiple domains directly from tracks without the need for different heuristics. MRPS is used to do single- and multi-ob...

Modeling and recognition of complex activities involving multiple, interacting objects in video is a significant problem in computer vision. In this paper, we examine activities using relative distances in phase space via pairwise analysis of all objects. This allows us to characterize simple interactions directly by modeling multi-object activitie...

In this paper, we focus on the problem of searching for complex activities involving multiple, interacting objects in video. We examine the dynamics of formation and dispersal of groups as well as their interactions with other groups and individuals. In order to establish a general formalism, we examine activities using relative distances in phase...

An identification of students' interests in biology can help teachers better engage their pupils and meet their needs. To this end, over 28,000 self-generated biological questions raised by students from kindergarten through graduate school were analyzed according to age and gender. The sample demonstrated a dominance of female contributions among...

In this paper, we propose a computational framework for integrating the physics of motion with the neurobiological basis of perception in order to model and recognize human actions and object activities. The essence, or gist, of an action is intrinsically related to the motion of the scene's objects. We define the Hamiltonian energy signature (HES)...

Nearly 79,000 questions sent to an Internet-based Ask-A-Scientist site during the last decade were analyzed according to the surfer's age, gender, country of origin, and the year the question was sent. The sample demonstrated a surprising dominance of female contributions among K-12 students (although this dominance did not carry over to the full s...

Interest is a powerful motivator; nonetheless, science educators often lack the necessary information to make use of the power of student-specific interests in the reform process of science curricula. This study suggests a novel methodology, which might be helpful in identifying such interests—using children's self-generated questions as an indicat...

This paper will describe a set of Physics Experiments that use selected Java and Shockwave Applets. They form a Laboratory course which augments the more conventional lectures in a Concepts of Physics course at Devry University in Pomona, California. The Laboratory has been Instructor-led but is sufficiently self-contained to be a part of a Virtual...

As the Internet evolves, it transforms human society in a multitude of ways. In fact, the possible effects of the Internet on human cognition and science education become apparent when examining how students use the Internet to learn about science. Our goal is to provide a positive social im-pact on science education and add societal value to how s...