Abstract

Field study of thermal comfort was conducted in six naturally ventilated hostel buildings of composite climate considering Class-II protocol of field measurement during summer 2011. Total 429 survey samples of same age group (average 19.6 years) were collected including objective and subjective measurements. Statistical analysis of student's responses and measured thermal environment variables was performed to determine existing indoor environmental conditions and priority of using behavioural controls. Thermal comfort indices were also calculated and compared to the student's perceptions. Neutral temperature was found to be 30.15 °C through regression analysis, with an average clothing of 0.41 Clo (min. 0.19 Clo, max 0.82 Clo). Results have shown a wide bandwidth of neutral temperatures (25.9–33.8 °C) for the hostel buildings which is higher than national/international standards of thermal comfort …

Abstract

In this paper, we show that certain phrases although not present in a given question/query, play a very important role in answering the question. Exploring the role of such phrases in answering questions not only reduces the dependency on matching question phrases for extracting answers, but also improves the quality of the extracted answers. Here matching question phrases means phrases which co-occur in given question and candidate answers. To achieve the above discussed goal, we introduce a bigram-based word graph model populated with semantic and topical relatedness of terms in the given document. Next, we apply an improved version of ranking with a prior-based approach, which ranks all words in the candidate document with respect to a set of root words (ie non-stopwords present in the question and in the candidate document). As a result, terms logically related to the root words are scored higher than terms that are not related to the root words. Experimental results show that our devised system performs better than state-of-the-art for the task of answering Why-questions.

Abstract

In this work, we propose a solution with sub-logarithmic query time for counting the number of maximal points in an axis parallel query rectangle. The problem has been previously studied in [3]and [5]. To the best of our knowledge, this is the first sub-logarithmic query time solution for the problem. Our model of computation is the word RAM with word size of Θ(logn) bits.

Abstract

In this paper, we propose an approach for the analysis and detection of acoustic events in speech signals using the Bessel series expansion. The acoustic events analyzed are the voice onset time (VOT) and the glottal closure instants (GCIs). The hypothesis is that the Bessel functions with their damped sinusoid-like basis functions are better suited for representing the speech signals than the sinusoidal basis functions used in the conventional Fourier representation. The speech signal is band-pass filtered by choosing the appropriate range of Bessel coefficients to obtain a narrow-band signal, which is decomposed further into amplitude modulated (AM) and frequency modulated (FM) components. The discrete energy separation algorithm (DESA) is used to compute the amplitude envelope (AE) of the narrow-band AM-FM signal. Events such as the consonant and vowel beginnings in an unvoiced stop consonant vowel (SCV) and the GCIs are derived by processing the AE of the signal. The proposed approach for the detection of the VOT using the Bessel expansion is shown to perform better than the conventional Fourier representation. The performance of the proposed GCI detection method using the Bessel series expansion is compared against some of the existing methods for various noise environments and signal-to-noise ratios.

Abstract

This paper initiates formal analysis of a simple, distributed algorithm for community detection on networks. We analyze an algorithm that we call Max-LPA, both in terms of its convergence time and in terms of the “quality” of the communities detected. Max-LPA is an instance of a class of community detection algorithms called label propagation algorithms. As far as we know, most analysis of label propagation algorithms thus far has been empirical in nature and in this paper we seek a theoretical understanding of label propagation algorithms. In our main result, we define a clustered version of Erdös-Rényi random graphs with clusters V 1, V 2, …, V k where the probability p, of an edge connecting nodes within a cluster V i is higher than p′, the probability of an edge connecting nodes in distinct clusters. We show that even with fairly general restrictions on p and p′ ( p=Ω(1n1/4−ϵ) for any ε > 0, p′ = O(p 2), where n is the number of nodes), Max-LPA detects the clusters V 1, V 2, …, V n in just two rounds. Based on this and on empirical results, we conjecture that Max-LPA can correctly and quickly identify communities on clustered Erdös-Rényi graphs even when the clusters are much sparser, i.e., with p=clognn for some c > 1.

Abstract

In this work we consider a quantum network consisting of nodes and entangled states connecting them. In every node there is a single player. The players at the intermediate nodes carry out measurements to produce an entangled state between the initial and final node. Here we address the problem that how much classical as well as quantum information can be sent from initial node to final node. In this context, we present strong theorems which state that how the teleportation capability of this remotely prepared state is linked up with the fidelities of teleportation of the resource states. Similarly, we analyze the super dense coding capacity of this remotely prepared state in terms of the capacities of the resource entangled states. However, we first obtain the relations involving the amount of entanglement of the resource states with the final state in terms concurrence. These relations are quite similar to the bounds obtained in references [G. Gour, Phys. Rev. A 71, 012318 (2005); G. Gour, B.C. Sanders, Phys. Rev. Lett. 93, 260501 (2005)]. More specifically, in an arbitrary quantum network when two nodes are not connected, our result shows how much information, both quantum and classical can be transmitted between these nodes. We show that the amount of transferable information depends on the capacities of the inter connecting entangled resources. These results have a tremendous future application in the context of determining the optimal path in a quantum network to send the maximal possible information.

Abstract

Diffusion Weighted Magnetic Resonance Imaging (DWI) is routinely used for early detection of cerebral ischemic changes in acute stroke. Fast acquisition with a standard echoplanar imaging technique generally compromises the image signal-to-noise ratio and in-plane resolution resulting in a reduction of the conspicuity and definition of lesions in the acquired data when viewed on a standard 8-bit display. We present a novel method for automatically and adaptively determining the window settings that enhance the contrast of the image relative to the ischemic lesions. The method performs a coarse segmentation of the lesions followed by contrast-to-noise ratio based computation of the optimal window parameters. The proposed method was tested on 24 datasets acquired with different protocols. The contrast improvement of the lesions is validated through a mirror region of interest analysis and by using the contrast improvement ratio metric. The average obtained improvement in contrast ranges from 25% to 60%. Preliminary results of segmentation showed a good reduction in the false positives and improvement in the lesion boundaries. A perception study of the windowed results against 8 radiologists was conducted. Reduction of 14.17% in the mean response time of detection was observed. Statistical analysis performed using t-test validates the reduction in mean response time to be significant. Results presented in the study show promise in the method.

Abstract

Population screening for sight threatening diseases based on fundus imaging is in place or being considered worldwide. Most existing programs are focussed on a specific disease and are based on manual reading of images, though automated image analysis based solutions are being developed. Exudates and drusen are bright lesions which indicate very different diseases, but can appear to be similar. Discriminating between them is of interest to increase screening performance. In this paper, we present a Bag of Words approach which can be used to design a system that can play the dual role of content based retrieval (of images with exudates or drusen) system and a decision support system to address the problem of bright lesion discrimination. The approach consists of a novel partitioning of an image into patches from which color, texture, edge and granulometry based features are extracted to build a dictionary. A bag of Words approach is then employed to help retrieve images matching a query image as well as derive a decision on the type of bright lesion in the given (query) image. This approach has been implemented and tested on a combination of public and local dataset of 415 images. The area under the curve for image classification is 0.90 and retrieved precision is 0.76.

Abstract

Recently Lee and Liu proposed an efficient password based authentication and key agreement scheme using smart card for the telecare medicine information system [J. Med. Syst. (2013) 37:9933]. In this paper, we show that though their scheme is efficient, their scheme still has two security weaknesses such as (1) it has design flaws in authentication phase and (2) it has design flaws in password change phase. In order to withstand these flaws found in Lee-Liu’s scheme, we propose an improvement of their scheme. Our improved scheme keeps also the original merits of Lee-Liu’s scheme. We show that our scheme is efficient as compared to Lee-Liu’s scheme. Further, through the security analysis, we show that our scheme is secure against possible known attacks. In addition, we simulate our scheme for the formal security verification using the widely-accepted AVISPA (Automated Validation of Internet Security Protocols and Applications) tool to show that our scheme is secure against passive and active attacks.

Abstract

Several key management schemes for access control in a user hierarchy have been proposed in the recent years. However, most of them have dealt with key management issues for tree structured hierarchies, which result overheads when they are applied to the linear hierarchies. Linear hierarchy comprises a particularly interesting type of hierarchies, and it appears in a wide range of applications such as secure communications within security corporations and multi-layered data streaming. In this paper, we propose an effective key management scheme for linear hierarchies. Compared to the recently proposed Hassen et al.'s scheme, our scheme reduces the storage overhead of each class significantly. Further, use of symmetric-key cryptosystem (Advanced Encryption Standard algorithm) makes the key sizes for security classes to reduce in our scheme. In addition, our scheme is secure against possible attacks required for a linear hierarchy access control scheme. Security along with low storage and computational overheads make our scheme to be much suitable for practical applications for linear hierarchies.