Mobile agent based TCP attacker identification in MANET using the traffic history (MAITH)

TCP attacks are the major problem faced by Mobile Ad hoc Networks (MANETs) due to its limited network and host resources. Attacker traceback is a promising solution which allows a victim to identify the exact location of the attacker and hence enables the victim to take proper countermeasure near attack origins, for forensics and to discourage attackers from launching the attacks. However, attacker traceback in MANET is a challenging problem due to dynamic network topology, limited network and host resources such as memory, bandwidth and battery life. We introduce a novel method of TCP attacker Identification in MANET using the Traffic History - MAITH. Based on the comprehensive evaluation based on simulations, we showed that MAITH can successfully track down the attacker under diverse mobile multi-hop network environment with low communication, computation, and memory overhead.

Compressive sensing for music signals: comparison of transforms with coherent dictionaries

Compressive Sensing (CS) is a new sensing paradigm which permits sampling of a signal at its intrinsic information rate which could be much lower than Nyquist rate, while guaranteeing good quality reconstruction for signals sparse in a linear transform domain. We explore the application of CS formulation to music signals. Since music signals comprise of both tonal and transient nature, we examine several transforms such as discrete cosine transform (DCT), discrete wavelet transform (DWT), Fourier basis and also non-orthogonal warped transforms to explore the effectiveness of CS theory and the reconstruction algorithms. We show that for a given sparsity level, DCT, overcomplete, and warped Fourier dictionaries result in better reconstruction, and warped Fourier dictionary gives perceptually better reconstruction. “MUSHRA” test results show that a moderate quality reconstruction is possible with about half the Nyquist sampling.

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.

FURTHER RECORDS OF THE SINDH AWL-HEADED SNAKE, Lytorhynchus paradoxus (GUNTHER, 1875), FROM INDIA WITH NOTES ON ITS HABITAT AND NATURAL HISTORY

This paper presents additional distributional records of the Sindh awl-headed snake Lytorhynchus paradoxus from India, along with scale counts, measurements and natural history observations of this poorly known species.

STUDENT'S-t MIXTURE MODEL BASED MULTI-INSTRUMENT RECOGNITION IN POLYPHONIC MUSIC

We address the problem of multi-instrument recognition in polyphonic music signals. Individual instruments are modeled within a stochastic framework using Student's-t Mixture Models (tMMs). We impose a mixture of these instrument models on the polyphonic signal model. No a priori knowledge is assumed about the number of instruments in the polyphony. The mixture weights are estimated in a latent variable framework from the polyphonic data using an Expectation Maximization (EM) algorithm, derived for the proposed approach. The weights are shown to indicate instrument activity. The output of the algorithm is an Instrument Activity Graph (IAG), using which, it is possible to find out the instruments that are active at a given time. An average F-ratio of 0 : 7 5 is obtained for polyphonies containing 2-5 instruments, on a experimental test set of 8 instruments: clarinet, flute, guitar, harp, mandolin, piano, trombone and violin.

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.

History of MRI

A brief account of the basic principle and methodologies of MRI technique, right from its beginning, are outlined. The final pulse sequence used for MRI using Fourier Imaging (phase encoding), Echo-Planar Imaging (EPI) for detection of a whole plane in a single excitation and T-1 and T-2 contrast enhancement is explained. The various associated methods such as, MR-spectroscopy, flow measurement (MRI-angiography), Lung-imaging using hyperpolarized Xe-129 and He-3 and functional imaging (f-MRI) are described.

History of Computing in India: 1955-2010

The history of computing in India is inextricably intertwined with two interacting forces: the political climate determined by the political party in power) and the government policies mainly driven by the technocrats and bureaucrats who acted within the boundaries drawn by the political party in power. There were four break points (which occurred in 1970, 1978, 1991 and 1998) that changed the direction of the development of computers and their applications. This article explains why these breaks occurred and how they affected the history of computing in India.

Dynamics of history-dependent epidemics in temporal networks

The structural properties of temporal networks often influence the dynamical processes that occur on these networks, e.g., bursty interaction patterns have been shown to slow down epidemics. In this paper, we investigate the effect of link lifetimes on the spread of history-dependent epidemics. We formulate an analytically tractable activity-driven temporal network model that explicitly incorporates link lifetimes. For Markovian link lifetimes, we use mean-field analysis for computing the epidemic threshold, while the effect of non-Markovian link lifetimes is studied using simulations. Furthermore, we also study the effect of negative correlation between the number of links spawned by an individual and the lifetimes of those links. Such negative correlations may arise due to the finite cognitive capacity of the individuals. Our investigations reveal that heavy-tailed link lifetimes slow down the epidemic, while negative correlations can reduce epidemic prevalence. We believe that our results help shed light on the role of link lifetimes in modulating diffusion processes on temporal networks.

MULTI-INSTRUMENT DETECTION IN POLYPHONIC MUSIC USING GAUSSIAN MIXTURE BASED FACTORIAL HMM

We formulate the problem of detecting the constituent instruments in a polyphonic music piece as a joint decoding problem. From monophonic data, parametric Gaussian Mixture Hidden Markov Models (GM-HMM) are obtained for each instrument. We propose a method to use the above models in a factorial framework, termed as Factorial GM-HMM (F-GM-HMM). The states are jointly inferred to explain the evolution of each instrument in the mixture observation sequence. The dependencies are decoupled using variational inference technique. We show that the joint time evolution of all instruments' states can be captured using F-GM-HMM. We compare performance of proposed method with that of Student's-t mixture model (tMM) and GM-HMM in an existing latent variable framework. Experiments on two to five polyphony with 8 instrument models trained on the RWC dataset, tested on RWC and TRIOS datasets show that F-GM-HMM gives an advantage over the other considered models in segments containing co-occurring instruments.

Interactions between reflection and praxis in the history of economic thought : the case of the franciscan circles from XIII century Assisi to the present

Resumen: Daniela Parisi analiza el impacto de la vida de San F rancisco de Asís desde la perspectiva de la historia del pensamiento económico. Haciendo referencia particularmente a la atención otorgada en los círculos franciscanos a los signos de los tiempos, la autora traza el camino desde la vida de San Francisco, pasando por la vida de la Orden hasta el presente, y revela los orígenes del movimiento franciscano como un intento de reforma social y religiosa. En primer lugar, el artículo presenta la vida que llevó San Francisco como una “pobreza material voluntaria” en el contexto de los cambios socio-económicos que tuvieron lugar en el siglo XIII, con el advenimiento de la sociedad comercial. Luego, explica cómo la propuesta de San Francisco creció hasta convertirse en una orden religiosa. Finalmente, el artículo intenta iluminar aquellos aspectos en que la Orden Franciscana puede todavía considerarse un signo de los tiempos a través de una existencia comprometida con la pobreza, eliminando lo superfluo de nuestra vida y viviendo en consonancia con el Evangelio.

Don Ramón Vega, enigmático rebelde de la ópera mexicana

Resumen: Un fortuito hallazgo del libreto manuscrito de la ópera El grito de Dolores, de Ramón Vega, compositor mexicano del siglo XIX, protagonizado por esta autora, desencadenó una serie de preguntas que hasta el presente no han sido respondidas a cabalidad por los estudios dedicados a la historia de la música en México. La investigación desarrollada con el propósito de situar el manuscrito encontrado en el contexto social y cultural del siglo de la Independencia y la exhaustiva pesquisa realizada en diferentes archivos históricos fructificaron en el descubrimiento de un vasto corpus de fuentes documentales actualmente desconocidas. La información que arrojó el análisis de estos documentos completó el conocimiento existente sobre la vida de Ramón Vega, permitió enderezar algunas ideas falibles en torno a su producción operística, así como construir y sustentar la hipótesis de que El grito de Dolores puede calificarse como el primer intento de creación de una ópera mexicana “enteramente nacional”.

The pottery from A and C-Group tombs at Serra West in the Museum of Natural History, La Plata

Abstract: The Museum of Natural History, La Plata, Argentina, houses a ceramic collection of the A-Group and C-Group cultures from Nubian tombs at Serra West (AA and ACS cemeteries), on the west bank of the Nile in Lower Nubia. It has been originated from the division after the excavations made by the Franco-Argentine Archaeological Expedition in Sudan between 1961 and 1963, as part of the UNESCO campaigns to save the Nubian monuments.