Abstract

The deterioration and loss of water bodies like lakes due to anthropogenic activities, are at the same pace at which forests are degraded. Lakes and ponds play a major role in the global cycle (carbon, water, etc.). They act as the basic units of hydrological systems to better understand the biogeochemical processes that take place within these aquatic systems and further for their management plans. As an initiative of managing resources at the unit level (lake) in the current study, we tried to understand the history and ecological dynamics of" Brahmayyalingam Cheruvu", a lake located in the peri-urban areas of the rapidly expanding Vijayawada city, Andhra Pradesh State, India. The study is based on field inventories, local surveys and satellite data, both current and past. Use of satellite images aided in capturing the changing spatiao-temporal lake dynamics due to climatic variations and government policy. The …

Abstract

In this work, we consider the problem of finding the closest pair (in L 1 metric) of points in an orthogonal query rectangle. Given a set of n static points on a U× U grid, we preprocess these points into a data structure of size O (m f (m) log 2 m) that can be queried in time O ((g (m)+ log log m) log 3 m), for m= O (n log U) and (i) f (m)= O (1) and g (m)= O (log ε m);(ii) f (m)= O (log log m) and g (m)= O (log log m);(iii) f (m)= O (log ε m) and g (m)= O (1). Here ε: 0< ε< 1 is a small but arbitrary constant.

Abstract

A t-ruling set of a graph G=(V, E) is a vertex-subset S⊆ V that is independent and satisfies the property that every vertex v∈ V is at a distance of at most t hops from some vertex in S. A maximal independent set (MIS) is a 1-ruling set. Extending results from Kothapalli et al.(FSTTCS 2012) this note presents a randomized algorithm for computing, with high probability, a t-ruling set in O (t⋅ log 1/(t-1) n) rounds for 2< t≤√(log log n) and in (O (√(log log n))) rounds for t>√(log log n).

Abstract

Range searching is a primal problem in computational geometry with applications to database systems, mobile computing, geographical information systems, and the like. Defined simply, the problem is to preprocess a given a set of points in a d-dimensional space so that the points that lie inside an orthogonal query rectangle can be efficiently reported. Many practical applications of range trees require one to process a massive amount of points and a massive number of queries. In this context, we propose an efficient parallel implementation of range trees on manycore architectures such as GPUs. We extend our implementation to query processing. While queries can be batched together to exploit interquery parallelism, we also utilize intra-query parallelism. This inter- and intra-query parallelism greatly reduces the per query latency thereby increasing the throughput. On an input of 1 M points in a 2-dimensional space, our implementation on a single Nvidia GTX 580 GPU for constructing a range tree shows an improvement of 12X over a 12-threaded CPU implementation. We also achieve an average throughput of 10 M queries per second for answering 4 M queries on a range tree containing 1 M points on a Nvidia GTX 580 GPU. We extend our implementation to an application where we seek to report the set of maximal points in a given orthogonal query rectangle.

Abstract

Multiplying a sparse matrix with a vector, denoted spmv, is a fundamental operation in linear algebra with several applications. Hence, efficient and scalable implementation of spmv has been a topic of immense research. Recent efforts are aimed at implementations on GPUs, multicore architectures, and such emerging computational platforms. Owing to the highly irregular nature of spmv, it is observed that GPUs and CPUs can offer comparable performance.

Abstract

In this work, we extensively study the problem of broadcasting of quantum correlations (QCs). This includes broadcasting of quantum entanglement as well as correlations that go beyond the notion of entanglement (QCsbE). It is quite well known from the “no-broadcasting theorem” that perfect broadcasting of QCs is not possible. However, it does not rule out the possibility of partial broadcasting of QCs where we can get lesser correlated states from a given correlated state. In order to have a holistic view of broadcasting, we investigate this problem by starting with a most general representation of two qubit mixed states in terms of the Bloch vectors. As a cloning transformation we have used universal symmetric optimal Buzek-Hillery (BH) cloner both locally and nonlocally. Unlike entanglement, we find that it is impossible to broadcast QCsbE optimally. Lastly, we generalize these results for any symmetric or asymmetric cloning machines as well. This result brings out a fundamental difference between the correlations defined from the perspective of entanglement and the correlations measure which claims to go beyond entanglement.

Abstract

We study the dynamics of quantum dissension for three qubit states in various dissipative channels such as amplitude damping, dephasing and depolarizing. Our study is solely based on Markovian environments where quantum channels are without memory and each qubit is coupled to its own environment. We start with mixed GHZ, mixed W, mixture of separable states, a mixed biseparable state, as the initial states and mostly observe that the decay of quantum dissension is asymptotic in contrast to sudden death of quantum entanglement in similar environments. This is a clear indication of the fact that quantum correlation in general is more robust against the effect of noise. However, for a given class of initial mixed states we find a temporary leap in quantum dissension for a certain interval of time. More precisely, we observe the revival of quantum correlation to happen for certain time period. This signifies that the measure of quantum correlation such as quantum discord, quantum dissension, defined from the information theoretic perspective is different from the correlation defined from the entanglement-separability paradigm and can increase under the effect of the local noise. We also study the effects of these channels on the monogamy score of each of these initial states. Interestingly, we find that for certain class of states and channels, there is change from negative values to positive values of the monogamy score with classical randomness as well as with time. This gives us an important insight in obtaining states which are freely sharable (polygamous state) from the states which are not freely sharable (monogamous). This is indeed a remarkable feature, as we can create monogamous states from polygamous states Monogamous states are considered to have more signatures of quantum ness and can be used for security purpose.

Abstract

Optic nerve head (ONH) segmentation problem has been of interest for automated glaucoma assessment. Although various segmentation methods have been proposed in the recent past, it is difficult to evaluate and compare the performance of individual methods due to a lack of a benchmark dataset. The problem of segmentation involves segmentation of optic disk and cup region within ONH region. Available datasets do not incorporate challenges present in this problem. In this data paper, we present a comprehensive dataset of retinal images which include both normal and glaucomatous eyes and manual segmentations from multiple human experts. Both area and boundary-based evaluation measures are presented to evaluate a method on various aspects relevant to the problem of glaucoma assessment.

Abstract

Optic disk (OD) and macula are anatomical structures in retinal images. Their detection is of interest in computer assisted diagnostic (CAD) algorithm development. We propose a joint detection algorithm which exploits the bilateral symmetry present in retinal images and present a method to detect OD and macula. A vessel density based metric is proposed to determine the axis of symmetry which is used along with appearance features and geometric constraint on the OD and macula for their detection. The proposed method has been evaluated on a large number of images drawn from 4 public and one private dataset. Obtained results show that our method has consistently high detection rate across the datasets. Since the detection is also very fast, the proposed method offers a good solution for CAD based disease screening.

Abstract

We present a novel framework for depth based optic cup boundary extraction from asingle2D color fundus photograph per eye.Multiple depth estimates from shading, color and texture gradients in the image are correlated with Optical Coherence Tomography (OCT)based depth using a coupled sparse dictionary, trained on image-depth pairs. Finally, a Markov Random Field is formulated on the depth map to model the relative depth and discontinuity at the cup boundary. Leave-one-out validation of depth estimation on the INSPIRE dataset gave average correlation coefficient of 0.80. Our cup segmentation out performs several state-of-the-art methods on the DRISHTI-GS dataset with an average F-score of 0.81 and boundary-error of 21.21 pixels on test set against manual expert markings. Evaluation on an additional set of 28images against OCT scanner provided ground truth showed an average rms error of 0.11 on Cup-Disk diameter and 0.19 on Cup-disk area ratios.