Finite data performance of MUSIC and minimum norm methods

In the direction of arrival (DOA) estimation problem, we encounter both finite data and insufficient knowledge of array characterization. It is therefore important to study how subspace-based methods perform in such conditions. We analyze the finite data performance of the multiple signal classification (MUSIC) and minimum norm (min. norm) methods in the presence of sensor gain and phase errors, and derive expressions for the mean square error (MSE) in the DOA estimates. These expressions are first derived assuming an arbitrary array and then simplified for the special case of an uniform linear array with isotropic sensors. When they are further simplified for the case of finite data only and sensor errors only, they reduce to the recent results given in [9-12]. Computer simulations are used to verify the closeness between the predicted and simulated values of the MSE.

Influence of strain rate and state-of-stress on the formation of ferrite in stainless steel type AISI 304 during hot working

The influence of strain rate and state-of-stress on the formation of ferrite in stainless steel type AISI 304L, 304 and 304 as-cast, during hot working has been studied. Compression and torsion tests were conducted in the temperature range 1100 to 1250 degrees C and strain rate range 0.001 to 100 s(-1) on these materials, Ferrite formation occurs during deformation at temperatures above 1150 degrees C and strain rates above 10 s(-1), in stainless steel type AISI 304L and 304. The tendency for the formation of ferrite is more in as-cast 304 than in wrought 304, In as-cast 304 the ferrite forms at lower temperatures and strain rates, The tendency for the ferrite formation is more in torsion than in compression.

Music and symbolic dynamics: the science behind an art

Music signals comprise of atomic notes drawn from a musical scale. The creation of musical sequences often involves splicing the notes in a constrained way resulting in aesthetically appealing patterns. We develop an approach for music signal representation based on symbolic dynamics by translating the lexicographic rules over a musical scale to constraints on a Markov chain. This source representation is useful for machine based music synthesis, in a way, similar to a musician producing original music. In order to mathematically quantify user listening experience, we study the correlation between the max-entropic rate of a musical scale and the subjective aesthetic component. We present our analysis with examples from the south Indian classical music system.

Assessing resilience and state-transition models with historical records of cheatgrass Bromus tectorum invasion in North American sagebrush-steppe

1. Resilience-based approaches are increasingly being called upon to inform ecosystem management, particularly in arid and semi-arid regions. This requires management frameworks that can assess ecosystem dynamics, both within and between alternative states, at relevant time scales. 2. We analysed long-term vegetation records from two representative sites in the North American sagebrush-steppe ecosystem, spanning nine decades, to determine if empirical patterns were consistent with resilience theory, and to determine if cheatgrass Bromus tectorum invasion led to thresholds as currently envisioned by expert-based state-and-transition models (STM). These data span the entire history of cheatgrass invasion at these sites and provide a unique opportunity to assess the impacts of biotic invasion on ecosystem resilience. 3. We used univariate and multivariate statistical tools to identify unique plant communities and document the magnitude, frequency and directionality of community transitions through time. Community transitions were characterized by 37-47% dissimilarity in species composition, they were not evenly distributed through time, their frequency was not correlated with precipitation, and they could not be readily attributed to fire or grazing. Instead, at both sites, the majority of community transitions occurred within an 8-10year period of increasing cheatgrass density, became infrequent after cheatgrass density peaked, and thereafter transition frequency declined. 4. Greater cheatgrass density, replacement of native species and indication of asymmetry in community transitions suggest that thresholds may have been exceeded in response to cheatgrass invasion at one site (more arid), but not at the other site (less arid). Asymmetry in the direction of community transitions also identified communities that were at-risk' of cheatgrass invasion, as well as potential restoration pathways for recovery of pre-invasion states. 5. Synthesis and applications. These results illustrate the complexities associated with threshold identification, and indicate that criteria describing the frequency, magnitude, directionality and temporal scale of community transitions may provide greater insight into resilience theory and its application for ecosystem management. These criteria are likely to vary across biogeographic regions that are susceptible to cheatgrass invasion, and necessitate more in-depth assessments of thresholds and alternative states, than currently available.

Disorder, oscillatory dynamics and state switching: the role of c-Myc

In this paper, using the intrinsically disordered oncoprotein Myc as an example, we present a mathematical model to help explain how protein oscillatory dynamics can influence state switching. Earlier studies have demonstrated that, while Myc overexpression can facilitate state switching and transform a normal cell into a cancer phenotype, its downregulation can reverse state-switching. A fundamental aspect of the model is that a Myc threshold determines cell fate in cells expressing p53. We demonstrate that a non-cooperative positive feedback loop coupled with Myc sequestration at multiple binding sites can generate bistable Myc levels. Normal quiescent cells with Myc levels below the threshold can respond to mitogenic signals to activate the cyclin/cdk oscillator for limited cell divisions but the p53/Mdm2 oscillator remains nonfunctional. In response to stress, the p53/Mdm2 oscillator is activated in pulses that are critical to DNA repair. But if stress causes Myc levels to cross the threshold, Myc inactivates the p53/Mdm2 oscillator, abrogates p53 pulses, and pushes the cyclin/cdk oscillator into overdrive sustaining unchecked proliferation seen in cancer. However, if Myc is downregulated, the cyclin/cdk oscillator is inactivated and the p53/Mdm2 oscillator is reset and the cancer phenotype is reversed. (C) 2015 Elsevier Ltd. All rights reserved.

Weighted subspace methods and spatial smoothing: analysis and comparison

The effect of using a spatially smoothed forward-backward covariance matrix on the performance of weighted eigen-based state space methods/ESPRIT, and weighted MUSIC for direction-of-arrival (DOA) estimation is analyzed. Expressions for the mean-squared error in the estimates of the signal zeros and the DOA estimates, along with some general properties of the estimates and optimal weighting matrices, are derived. A key result is that optimally weighted MUSIC and weighted state-space methods/ESPRIT have identical asymptotic performance. Moreover, by properly choosing the number of subarrays, the performance of unweighted state space methods can be significantly improved. It is also shown that the mean-squared error in the DOA estimates is independent of the exact distribution of the source amplitudes. This results in a unified framework for dealing with DOA estimation using a uniformly spaced linear sensor array and the time series frequency estimation problems.

Automatic Tonic Identification in Indian Art Music: Approaches and Evaluation

The tonic is a fundamental concept in Indian art music. It is the base pitch, which an artist chooses in order to construct the melodies during a rg(a) rendition, and all accompanying instruments are tuned using the tonic pitch. Consequently, tonic identification is a fundamental task for most computational analyses of Indian art music, such as intonation analysis, melodic motif analysis and rg recognition. In this paper we review existing approaches for tonic identification in Indian art music and evaluate them on six diverse datasets for a thorough comparison and analysis. We study the performance of each method in different contexts such as the presence/absence of additional metadata, the quality of audio data, the duration of audio data, music tradition (Hindustani/Carnatic) and the gender of the singer (male/female). We show that the approaches that combine multi-pitch analysis with machine learning provide the best performance in most cases (90% identification accuracy on average), and are robust across the aforementioned contexts compared to the approaches based on expert knowledge. In addition, we also show that the performance of the latter can be improved when additional metadata is available to further constrain the problem. Finally, we present a detailed error analysis of each method, providing further insights into the advantages and limitations of the methods.

On plane-wave propagation in a uniform pipe in the presence of a mean flow and a temperature gradient

A theoretical study on the propagation of plane waves in the presence of a hot mean flow in a uniform pipe is presented. The temperature variation in the pipe is taken to be a linear temperature gradient along the axis. The theoretical studies include the formulation of a wave equation based on continuity, momentum, and state equation, and derivation of a general four-pole matrix, which is shown to yield the well-known transfer matrices for several other simpler cases.

A speech-music discriminator using HILN model based features

We propose a simple speech music discriminator that uses features based on HILN(Harmonics, Individual Lines and Noise) model. We have been able to test the strength of the feature set on a standard database of 66 files and get an accuracy of around 97%. We also have tested on sung queries and polyphonic music and have got very good results. The current algorithm is being used to discriminate between sung queries and played (using an instrument like flute) queries for a Query by Humming(QBH) system currently under development in the lab.

Achieving sustainable transportation system for Indian cities - problems and issues

This article aims at identifying the research issues and challenges that need to be addressed to achieve sustainable transportation system for Indian cities. The same is achieved by understanding the current system and trends of urbanization, motorization and modal shares in India; and their impact on mobility and safety (the two basic goals of transportation) as well as environment. Further, the article explores the efforts by the central and state governments in India to address the sustainability issues, and the problems and issues over and above the present efforts to achieve sustainability. The article concludes by summarizing the research issues with respect to planning/modelling, non-motorized transport, public transport, driver behaviour and road safety and traffic management. It is expected that these research issues will provide potential directions for carrying out further research aimed at achieving sustainable transport system for Indian cities.

Query Click and Text Similarity Graph for Query Suggestions

Query suggestion is an important feature of the search engine with the explosive and diverse growth of web contents. Different kind of suggestions like query, image, movies, music and book etc. are used every day. Various types of data sources are used for the suggestions. If we model the data into various kinds of graphs then we can build a general method for any suggestions. In this paper, we have proposed a general method for query suggestion by combining two graphs: (1) query click graph which captures the relationship between queries frequently clicked on common URLs and (2) query text similarity graph which finds the similarity between two queries using Jaccard similarity. The proposed method provides literally as well as semantically relevant queries for users' need. Simulation results show that the proposed algorithm outperforms heat diffusion method by providing more number of relevant queries. It can be used for recommendation tasks like query, image, and product suggestion.