Divergencies of Perception : The Possibilities of Merleau-Pontian Phenomenology in Analyses of Contemporary Art

Maurice Merleau-Ponty (1908-1961) has been known as the philosopher of painting. His interest in the theory of perception intertwined with the questions concerning the artist s perception, the experience of an artwork and the possible interpretations of the artwork. For him, aesthetics was not a sub-field of philosophy, and art was not simply a subject matter for the aesthetic experience, but a form of thinking. This study proposes an opening for a dialogue between Merleau-Pontian phenomenology and contemporary art. The thesis examines his phenomenology through certain works of contemporary art and presents readings of these artworks through his phenomenology. The thesis both shows the potentiality of a method, but also engages in the critical task of finding the possible limitations of his approach. The first part lays out the methodological and conceptual points of departure of Merleau-Ponty s phenomenological approach to perception as well as the features that determined his discussion on encountering art. Merleau-Ponty referred to the experience of perceiving art using the notion of seeing with (voir selon). He stressed a correlative reciprocity described in Eye and Mind (1961) as the switching of the roles of the visible and the painter. The choice of artworks is motivated by certain restrictions in the phenomenological readings of visual arts. The examined works include paintings by Tiina Mielonen, a photographic work by Christian Mayer, a film by Douglas Gordon and Philippe Parreno, and an installation by Monika Sosnowska. These works resonate with, and challenge, his phenomenological approach. The chapters with case studies take up different themes that are central to Merleau-Ponty s phenomenology: space, movement, time, and touch. All of the themes are interlinked with the examined artworks. There are also topics that reappear in the thesis, such as the notion of écart and the question of encountering the other. As Merleau-Ponty argued, the sphere of art has a particular capability to address our being in the world. The thesis presents an interpretation that emphasises the notion of écart, which refers to an experience of divergence or dispossession. The sudden dissociation, surprise or rupture that is needed in order for a meeting between the spectator and the artwork, or between two persons, to be possible. Further, the thesis suggests that through artworks it is possible to take into consideration the écart, the divergence, that defines our subjectivity.

Prediction of the Indian summer monsoon rainfall using a state-of-the-art coupled ocean-atmosphere model

A state-of-the-art model of the coupled ocean-atmosphere system, the climate forecast system (CFS), from the National Centres for Environmental Prediction (NCEP), USA, has been ported onto the PARAM Padma parallel computing system at the Centre for Development of Advanced Computing (CDAC), Bangalore and retrospective predictions for the summer monsoon (June-September) season of 2009 have been generated, using five initial conditions for the atmosphere and one initial condition for the ocean for May 2009. Whereas a large deficit in the Indian summer monsoon rainfall (ISMR; June-September) was experienced over the Indian region (with the all-India rainfall deficit by 22% of the average), the ensemble average prediction was for above-average rainfall during the summer monsoon. The retrospective predictions of ISMR with CFS from NCEP for 1981-2008 have been analysed. The retrospective predictions from NCEP for the summer monsoon of 1994 and that from CDAC for 2009 have been compared with the simulations for each of the seasons with the stand-alone atmospheric component of the model, the global forecast system (GFS), and observations. It has been shown that the simulation with GFS for 2009 showed deficit rainfall as observed. The large error in the prediction for the monsoon of 2009 can be attributed to a positive Indian Ocean Dipole event seen in the prediction from July onwards, which was not present in the observations. This suggests that the error could be reduced with improvement of the ocean model over the equatorial Indian Ocean.

Microstructure evolution during solidification of DRMMCs (discontinuously reinforced metal matrix composites): State of art

Distribution of particle reinforcements in cast composites is determined by the morphology of the solidification front. Interestingly, during solidification, the morphology of the interface is intrinsically affected by the presence of dispersed reinforcements. Thus the dispersoid distribution and length scale of matrix microstructure is a result of the interplay between these two. A proper combination of material and process parameters can be used to obtain composites with tailored microstructures. This requires the generation of a broad data base and optimization of the complete solidification process. The length scale of soldification microtructure has a large influence on the mechanical properties of the composites. This presentation addresses the concept of a particle distribution map which can help in predicting particle distribution under different solidification conditions Future research directions have also been indicated.

Electron Cyclotron Resonance in Strained Si and Si0.94Ge0.06 Channels on Relaxed Si0.62Ge0.38 Buffers Grown by Rapid Thermal Chemical Vapor Deposition

We report the far-infrared measurements of the electron cyclotron resonance absorption in n-type Si/Si0. 62Ge0.38 and Si0.94Ge0.06 /Si0. 62Ge0.38 modulation- doped heterostructures grown by rapid thermal chemical vapor deposition. The strained Si and Si0.94Ge0.06 channels were grown on relaxed Si0.62Ge0.38 buffer layers, which consist of 0.6 μm uniform Si0.62Ge0.38 layers and 0.5 μm compositionally graded relaxed SiGe layers from 0% Ge to 38 % Ge. The buffer layers were annealed at 800 °C for 1 hr to obtain complete relaxation. The samples had 100 Å spacers and 300 Å 2×1019 cm-3 n-type supply layers on the tops of the 75 Å channels. The far-infrared measurements of electron cyclotron resonance were performed at 4K with the magnetic field of 4 – 8 Tesla. The effective masses determined from the slope of center frequency of absorption peak vs applied magnetic field plot are 0.20 mo and 0.19 mo for the two dimensional electron gases in the Si and Si0.94Ge0.06 channels, respectively. The Si effective mass is very close to that of two dimensional electron gas in Si MOSFET (0.198mo). The electron effective mass of Si0.94Ge0.06 is reported for the first time and about 5 % lower than that of pure Si.

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.

Generation of extended light-sheets for single and multi-photon fluorescence microscopy

We theoretically propose and computationally demonstrate the generation of extended light-sheet for fluorescence microscopy. This is made possible by the introduction of a specially designed double-window spatial filter that allows the light to pass through the periphery and center of a cylindrical lens. When illuminated with a plane wave, the proposed filter results in an extended depth-of-focus along with side-lobes which are due to other interferences in the transverse focal plane. Computational studies show a maximum extension of light-sheet by 3.38 times for single photon excitation and 3.68 times for multiphoton excitation as compared to state-of-art single plane illumination microscopy system. This technique may facilitate the study of large biological specimens (such as Zebrafish embryo and tissue) with high spatial resolution and reduced photobleaching. (C) 2013 AIP Publishing LLC.

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.

Progress in tuberculosis vaccine development and host-directed therapies-a state of the art review

Tuberculosis continues to kill 1.4 million people annually. During the past 5 years, an alarming increase in the number of patients with multidrug-resistant tuberculosis and extensively drug-resistant tuberculosis has been noted, particularly in eastern Europe, Asia, and southern Africa. Treatment outcomes with available treatment regimens for drug-resistant tuberculosis are poor. Although substantial progress in drug development for tuberculosis has been made, scientific progress towards development of interventions for prevention and improvement of drug treatment outcomes have lagged behind. Innovative interventions are therefore needed to combat the growing pandemic of multidrug-resistant and extensively drug-resistant tuberculosis. Novel adjunct treatments are needed to accomplish improved cure rates for multidrug-resistant and extensively drug-resistant tuberculosis. A novel, safe, widely applicable, and more effective vaccine against tuberculosis is also desperately sought to achieve disease control. The quest to develop a universally protective vaccine for tuberculosis continues. So far, research and development of tuberculosis vaccines has resulted in almost 20 candidates at different stages of the clinical trial pipeline. Host-directed therapies are now being developed to refocus the anti-Mycobacterium tuberculosis-directed immune responses towards the host; a strategy that could be especially beneficial for patients with multidrug-resistant tuberculosis or extensively drug-resistant tuberculosis. As we are running short of canonical tuberculosis drugs, more attention should be given to host-directed preventive and therapeutic intervention measures.

A coupled discriminative dictionary and transformation learning approach with applications to cross domain matching

Cross domain and cross-modal matching has many applications in the field of computer vision and pattern recognition. A few examples are heterogeneous face recognition, cross view action recognition, etc. This is a very challenging task since the data in two domains can differ significantly. In this work, we propose a coupled dictionary and transformation learning approach that models the relationship between the data in both domains. The approach learns a pair of transformation matrices that map the data in the two domains in such a manner that they share common sparse representations with respect to their own dictionaries in the transformed space. The dictionaries for the two domains are learnt in a coupled manner with an additional discriminative term to ensure improved recognition performance. The dictionaries and the transformation matrices are jointly updated in an iterative manner. The applicability of the proposed approach is illustrated by evaluating its performance on different challenging tasks: face recognition across pose, illumination and resolution, heterogeneous face recognition and cross view action recognition. Extensive experiments on five datasets namely, CMU-PIE, Multi-PIE, ChokePoint, HFB and IXMAS datasets and comparisons with several state-of-the-art approaches show the effectiveness of the proposed approach. (C) 2015 Elsevier B.V. All rights reserved.

A coupled discriminative dictionary and transformation learning approach with applications to cross domain matching

Cross domain and cross-modal matching has many applications in the field of computer vision and pattern recognition. A few examples are heterogeneous face recognition, cross view action recognition, etc. This is a very challenging task since the data in two domains can differ significantly. In this work, we propose a coupled dictionary and transformation learning approach that models the relationship between the data in both domains. The approach learns a pair of transformation matrices that map the data in the two domains in such a manner that they share common sparse representations with respect to their own dictionaries in the transformed space. The dictionaries for the two domains are learnt in a coupled manner with an additional discriminative term to ensure improved recognition performance. The dictionaries and the transformation matrices are jointly updated in an iterative manner. The applicability of the proposed approach is illustrated by evaluating its performance on different challenging tasks: face recognition across pose, illumination and resolution, heterogeneous face recognition and cross view action recognition. Extensive experiments on five datasets namely, CMU-PIE, Multi-PIE, ChokePoint, HFB and IXMAS datasets and comparisons with several state-of-the-art approaches show the effectiveness of the proposed approach. (C) 2015 Elsevier B.V. All rights reserved.