Geetha Seethakuttyamma

Bio: Geetha Seethakuttyamma is an academic researcher. The author has contributed to research in topics: Induced path & Betweenness centrality. The author has an hindex of 2, co-authored 2 publications receiving 18 citations.

Convexity in partial cubes: the hull number

Abstract: We prove that the combinatorial optimization problem of determining the hull number of a partial cube is NP-complete. This makes partial cubes the minimal graph class for which NP-completeness of this problem is known and improves some earlier results in the literature. On the other hand we provide a polynomial-time algorithm to determine the hull number of planar partial cube quadrangulations. Instances of the hull number problem for partial cubes described include poset dimension and hitting sets for interiors of curves in the plane. To obtain the above results, we investigate convexity in partial cubes and characterize these graphs in terms of their lattice of convex subgraphs, improving a theorem of Handa. Furthermore we provide a topological representation theorem for planar partial cubes, generalizing a result of Fukuda and Handa about rank three oriented matroids.

Two Tell-tale Perspectives of PTSD: Neurobiological Abnormalities and Bayesian Regulatory Network of the Underlying Disorder in a Refugee Context

Abstract: Global refugee crisis around the world has displaced millions of people from their homes. Although some of them adjust well, many suffer from significant psychological distress, such as post-traumatic stress disorder (PTSD), owing to exposure to traumatic events and hardships. Here, diagnosis and access to psychological health care present particular challenges for various human-centered design issues. Therefore, analyzing the case of Rohingya refugees in Bangladesh, we propose a two-way diagnosis of PTSD using (i) short inexpensive questionnaire to determine its prevalence, and (ii) low-cost portable EEG headset to identify potential neurobiological markers of PTSD. To the best of our knowledge, this study is the first to use consumer-grade EEG devices in the scarce-resource settings of refugees. Moreover, we explored the underlying structure of PTSD and its symptoms via developing various hybrid models based on Bayesian inference by combining aspects from both reflective and formative models of PTSD, which is also the first of its kind. Our findings revealed several key components of PTSD and its neurobiological abnormality. Moreover, challenges faced during our study would inform design processes of screening tools and treatments of PTSD to incorporate refugee experience in a more meaningful way during contemporary and future humanitarian crisis.

Axiomatization of betweenness in order-theoretic trees

Abstract: The ternary betweenness relation of a tree, B(x,y,z) expresses that y is on the unique path between x and z. This notion can be extended to order-theoretic trees defined as partial orders such that the set of nodes larger than any node is linearly ordered. In such generalized trees, the unique "path" between two nodes can have infinitely many nodes. We generalize some results obtained in a previous article for the betweenness of join-trees. Join-trees are order-theoretic trees such that any two nodes have a least upper-bound. The motivation was to define conveniently the rank-width of a countable graph. We called quasi-tree the structure based on the betweenness relation of a join-tree. We proved that quasi-trees are axiomatized by a first-order sentence. Here, we obtain a monadic second-order axiomatization of betweenness in order-theoretic trees. We also define and compare several induced betweenness relations, i.e., restrictions to sets of nodes of the betweenness relations in generalized trees of different kinds. We prove that induced betweenness in quasi-trees is characterized by a first-order sentence. The proof uses order-theoretic trees.