Représenter et construire la psychiatrie en France, 1801-1863 : l'art des premiers aliénistes

Depuis les quatre dernières décennies, des publications célèbres analysent l’histoire, l’art et l’architecture de la psychiatrie de la fin du dix-neuvième siècle afin de dénoncer les aspects négatifs de la science psychiatrique : voyeurisme sur la personne du fou, déshumanisation de l’asile, autoglorification du psychiatre, abus de pouvoir. C’est ce regard à sens unique que j’ai voulu déjouer dans cette thèse en consacrant ma recherche aux œuvres produites en amont de cette période. Leur analyse a permis de prendre conscience de l’autre versant de la science psychiatrique, celui qui est philanthropique, bienveillant et animé d’un réel espoir de guérison. Mon objectif a été de construire, par l’analyse de ce domaine iconographique inédit ou négligé, une nouvelle histoire de la naissance de la psychiatrie, celle de sa culture visuelle. Une histoire qui révèle ses idéaux du début du siècle et les écarts à ses propres aspirations par son besoin de légitimation et de professionnalisation. Ma thèse propose une enquête épistémologique de l’histoire de l’aliénisme français, par le biais du discours porté par les œuvres d’art commandées par ses fondateurs. Le premier chapitre est consacré aux premiers asiles conçus comme le prolongement du corps du psychiatre et ils sont analysés selon les valeurs de la nouvelle science. Je me suis appliquée à y démontrer que le concept même d’asile, agissant sur nos sensations et sur notre cognition, relève autant des théories architecturales des Lumières que des besoins spécifiques de l’aliénisme. Le deuxième chapitre identifie, pour la première fois, un ensemble de portraits de la première génération d’aliénistes et de leurs disciples. J’argumente que ce corpus voulait imposer l’image de l’aliéniste comme modèle de raison et établir sa profession. Pour ce faire, il s’éloigne des premières représentations des aliénistes, paternalistes, et philanthropiques. Le troisième chapitre analyse les représentations des aliénés produites pour les traités fondateurs de la psychiatrie publiés en France. Le vecteur de mon analyse et le grand défi pour l’art et la science viennent de l’éthique des premiers psychiatres : comment représenter la maladie mentale sans réduire le malade à un être essentiellement autre ? Une première phase de production accorde à l’aliéné autonomie et subjectivité. Mais la nécessité d’objectiver le malade pour répondre aux besoins scientifiques de l’aliénisme a, à nouveau, relégué l’aliéné à l’altérité. Le sujet du quatrième et dernier chapitre est le cycle décoratif de la chapelle de l’hospice de Charenton (1844-1846), principal asile parisien de l’époque. J’y interroge comment l’art religieux a pu avoir un rôle face à la psychiatrie, en empruntant à l’iconographie religieuse sa force et sa puissance pour manifester l’autorité de l’aliéniste jusque dans la chapelle de l’asile. Le dix-neuvième siècle a été porteur d’espoirs en la reconnaissance de la liberté des êtres et de l’égalité des droits entre les personnes. Ces espoirs ont pourtant été déçus et les œuvres de l’aliénisme montrent un nouvel aspect de ces promesses non tenues envers les groupes fragilisés de la société, promesses de reconnaissance de leur subjectivité, de leur autonomie et de leur dignité.

L’ontologie du non-humain en Amazonie selon les écrits de Philippe Descola et d’Eduardo Viveiros de Castro

Le non-humain et son ontologie sont définis dans ce mémoire en fonction des écrits de Philippe Descola et d’Eduardo Viveiros de Castro, deux figures-clés en anthropologie contemporaine sur l’Amazonie. L’animisme de Descola prête aux non-humains une intériorité humaine et les différencie par leur corps. Le perspectivisme de Viveiros de Castro, quant à lui, suppose que les points de vue différents créent des mondes et établissent ce qui est humain ou non. L’humain correspond au sujet cosmologique à la position pronominale de la première personne du singulier, ou « I », au sein d’une relation. De la sorte, un non-humain se perçoit comme un humain à cette position pronominale « I » et voit l’Autre à la position pronominale « it », position du non-humain. Dans ces deux ontologies, le non-humain est conçu comme une personne capable d’agir dans les mondes. La diversité des êtres inclus dans cette ontologie relationnelle est démontrée par des illustrations provenant de l’ethnographie achuar et araweté de ces deux auteurs. Puis, les relations de parenté, d’alliance et de prédation que les non-humains tissent entre eux et avec les humains exposent l’homologie des rapports non-humains avec les rapports humains. Finalement, l’analyse des méthodes de communication entre le non-humain et l’humain élucide comment la reconnaissance du non-humain dans une communication permet le traitement de ces êtres en tant qu’humains. Le non-humain ne serait donc pas un sujet permanent, mais temporaire le moment de l’interaction.

Design of Cyclophanes: Synthesis and Study of Photophysical and Biomolecular Recognition Properties

Development of organic molecules that exhibit selective interactions with different biomolecules has immense significance in biochemical and medicinal applications. In this context, our main objective has been to design a few novel functionaIized molecules that can selectively bind and recognize nucleotides and DNA in the aqueous medium through non-covalent interactions. Our strategy was to design novel cycIophane receptor systems based on the anthracene chromophore linked through different bridging moieties and spacer groups. It was proposed that such systems would have a rigid structure with well defined cavity, wherein the aromatic chromophore can undergo pi-stacking interactions with the guest molecules. The viologen and imidazolium moieties have been chosen as bridging units, since such groups, can in principle, could enhance the solubility of these derivatives in the aqueous medium as well as stabilize the inclusion complexes through electrostatic interactions.We synthesized a series of water soluble novel functionalized cyclophanes and have investigated their interactions with nucleotides, DNA and oligonucIeotides through photophysical. chiroptical, electrochemical and NMR techniques. Results indicate that these systems have favorable photophysical properties and exhibit selective interactions with ATP, GTP and DNA involving electrostatic. hydrophobic and pi-stacking interactions inside the cavity and hence can have potential use as probes in biology.

A Writer Identification System For Handwritten Malayalam Documents

Handwriting is an acquired tool used for communication of one's observations or feelings. Factors that inuence a person's handwriting not only dependent on the individual's bio-mechanical constraints, handwriting education received, writing instrument, type of paper, background, but also factors like stress, motivation and the purpose of the handwriting. Despite the high variation in a person's handwriting, recent results from different writer identification studies have shown that it possesses sufficient individual traits to be used as an identification method. Handwriting as a behavioral biometric has had the interest of researchers for a long time. But recently it has been enjoying new interest due to an increased need and effort to deal with problems ranging from white-collar crime to terrorist threats. The identification of the writer based on a piece of handwriting is a challenging task for pattern recognition. The main objective of this thesis is to develop a text independent writer identification system for Malayalam Handwriting. The study also extends to developing a framework for online character recognition of Grantha script and Malayalam characters

Design Of Metal Architectures: Synthesis And Study Of Their Photophysical And Biomolecular Recognition Properties

Design and study of molecular receptors capable of mimicking natural processes has found applications in basic research as well as in the development of potentially useful technologies. Of the various receptors reported, the cyclophanes are known to encapsulate guest molecules in their cavity utilizing various non–covalent interactions resulting in significant changes in their optical properties. This unique property of the cyclophanes has been widely exploited for the development of selective and sensitive probes for a variety of guest molecules including complex biomolecules. Further, the incorporation of metal centres into these systems added new possibilities for designing receptors such as the metallocyclophanes and transition metal complexes, which can target a large variety of Lewis basic functional groups that act as selective synthetic receptors. The ligands that form complexes with the metal ions, and are capable of further binding to Lewis-basic substrates through open coordination sites present in various biomolecules are particularly important as biomolecular receptors. In this context, we synthesized a few anthracene and acridine based metal complexes and novel metallocyclophanes and have investigated their photophysical and biomolecular recognition properties.

COMBINED FEATURE EXTRACTION TECHNIQUES AND NAIVE BAYES CLASSIFIER FOR SPEECH RECOGNITION

Speech processing and consequent recognition are important areas of Digital Signal Processing since speech allows people to communicate more natu-rally and efficiently. In this work, a speech recognition system is developed for re-cognizing digits in Malayalam. For recognizing speech, features are to be ex-tracted from speech and hence feature extraction method plays an important role in speech recognition. Here, front end processing for extracting the features is per-formed using two wavelet based methods namely Discrete Wavelet Transforms (DWT) and Wavelet Packet Decomposition (WPD). Naive Bayes classifier is used for classification purpose. After classification using Naive Bayes classifier, DWT produced a recognition accuracy of 83.5% and WPD produced an accuracy of 80.7%. This paper is intended to devise a new feature extraction method which produces improvements in the recognition accuracy. So, a new method called Dis-crete Wavelet Packet Decomposition (DWPD) is introduced which utilizes the hy-brid features of both DWT and WPD. The performance of this new approach is evaluated and it produced an improved recognition accuracy of 86.2% along with Naive Bayes classifier.

IRIS BIOMETRIC RECOGNITION SYSTEM EMPLOYING CANNY OPERATOR

Biometrics has become important in security applications. In comparison with many other biometric features, iris recognition has very high recognition accuracy because it depends on iris which is located in a place that still stable throughout human life and the probability to find two identical iris's is close to zero. The identification system consists of several stages including segmentation stage which is the most serious and critical one. The current segmentation methods still have limitation in localizing the iris due to circular shape consideration of the pupil. In this research, Daugman method is done to investigate the segmentation techniques. Eyelid detection is another step that has been included in this study as a part of segmentation stage to localize the iris accurately and remove unwanted area that might be included. The obtained iris region is encoded using haar wavelets to construct the iris code, which contains the most discriminating feature in the iris pattern. Hamming distance is used for comparison of iris templates in the recognition stage. The dataset which is used for the study is UBIRIS database. A comparative study of different edge detector operator is performed. It is observed that canny operator is best suited to extract most of the edges to generate the iris code for comparison. Recognition rate of 89% and rejection rate of 95% is achieved

PERFORMANCE OF DIFFERENT CLASSIFIERS IN SPEECH RECOGNITION

Speech is the most natural means of communication among human beings and speech processing and recognition are intensive areas of research for the last five decades. Since speech recognition is a pattern recognition problem, classification is an important part of any speech recognition system. In this work, a speech recognition system is developed for recognizing speaker independent spoken digits in Malayalam. Voice signals are sampled directly from the microphone. The proposed method is implemented for 1000 speakers uttering 10 digits each. Since the speech signals are affected by background noise, the signals are tuned by removing the noise from it using wavelet denoising method based on Soft Thresholding. Here, the features from the signals are extracted using Discrete Wavelet Transforms (DWT) because they are well suitable for processing non-stationary signals like speech. This is due to their multi- resolutional, multi-scale analysis characteristics. Speech recognition is a multiclass classification problem. So, the feature vector set obtained are classified using three classifiers namely, Artificial Neural Networks (ANN), Support Vector Machines (SVM) and Naive Bayes classifiers which are capable of handling multiclasses. During classification stage, the input feature vector data is trained using information relating to known patterns and then they are tested using the test data set. The performances of all these classifiers are evaluated based on recognition accuracy. All the three methods produced good recognition accuracy. DWT and ANN produced a recognition accuracy of 89%, SVM and DWT combination produced an accuracy of 86.6% and Naive Bayes and DWT combination produced an accuracy of 83.5%. ANN is found to be better among the three methods.

k-NN based On-Line Handwritten Character recognition system

On-line handwriting recognition has been a frontier area of research for the last few decades under the purview of pattern recognition. Word processing turns to be a vexing experience even if it is with the assistance of an alphanumeric keyboard in Indian languages. A natural solution for this problem is offered through online character recognition. There is abundant literature on the handwriting recognition of western, Chinese and Japanese scripts, but there are very few related to the recognition of Indic script such as Malayalam. This paper presents an efficient Online Handwritten character Recognition System for Malayalam Characters (OHR-M) using K-NN algorithm. It would help in recognizing Malayalam text entered using pen-like devices. A novel feature extraction method, a combination of time domain features and dynamic representation of writing direction along with its curvature is used for recognizing Malayalam characters. This writer independent system gives an excellent accuracy of 98.125% with recognition time of 15-30 milliseconds

An Online Character Recognition System to Convert Grantha Script to Malayalam

This paper presents a novel approach to recognize Grantha, an ancient script in South India and converting it to Malayalam, a prevalent language in South India using online character recognition mechanism. The motivation behind this work owes its credit to (i) developing a mechanism to recognize Grantha script in this modern world and (ii) affirming the strong connection among Grantha and Malayalam. A framework for the recognition of Grantha script using online character recognition is designed and implemented. The features extracted from the Grantha script comprises mainly of time-domain features based on writing direction and curvature. The recognized characters are mapped to corresponding Malayalam characters. The framework was tested on a bed of medium length manuscripts containing 9-12 sample lines and printed pages of a book titled Soundarya Lahari writtenin Grantha by Sri Adi Shankara to recognize the words and sentences. The manuscript recognition rates with the system are for Grantha as 92.11%, Old Malayalam 90.82% and for new Malayalam script 89.56%. The recognition rates of pages of the printed book are for Grantha as 96.16%, Old Malayalam script 95.22% and new Malayalam script as 92.32% respectively. These results show the efficiency of the developed system

Face Recognition using Probabilistic Neural Networks

In this paper we address the problem of face detection and recognition of grey scale frontal view images. We propose a face recognition system based on probabilistic neural networks (PNN) architecture. The system is implemented using voronoi/ delaunay tessellations and template matching. Images are segmented successfully into homogeneous regions by virtue of voronoi diagram properties. Face verification is achieved using matching scores computed by correlating edge gradients of reference images. The advantage of classification using PNN models is its short training time. The correlation based template matching guarantees good classification results

Face Recognition using Probabilistic Neural Networks

n this paper we address the problem of face detection and recognition of grey scale frontal view images. We propose a face recognition system based on probabilistic neural networks (PNN) architecture. The system is implemented using voronoi/ delaunay tessellations and template matching. Images are segmented successfully into homogeneous regions by virtue of voronoi diagram properties. Face verification is achieved using matching scores computed by correlating edge gradients of reference images. The advantage of classification using PNN models is its short training time. The correlation based template matching guarantees good classification results.

Speech Recognition of Malayalam Numbers

Digit speech recognition is important in many applications such as automatic data entry, PIN entry, voice dialing telephone, automated banking system, etc. This paper presents speaker independent speech recognition system for Malayalam digits. The system employs Mel frequency cepstrum coefficient (MFCC) as feature for signal processing and Hidden Markov model (HMM) for recognition. The system is trained with 21 male and female voices in the age group of 20 to 40 years and there was 98.5% word recognition accuracy (94.8% sentence recognition accuracy) on a test set of continuous digit recognition task.

Handwritten Character Recognition of South Indian Scripts: A Review

Handwritten character recognition is always a frontier area of research in the field of pattern recognition and image processing and there is a large demand for OCR on hand written documents. Even though, sufficient studies have performed in foreign scripts like Chinese, Japanese and Arabic characters, only a very few work can be traced for handwritten character recognition of Indian scripts especially for the South Indian scripts. This paper provides an overview of offline handwritten character recognition in South Indian Scripts, namely Malayalam, Tamil, Kannada and Telungu