Investigations on some amino acid based single crystals for nonlinear optical applications and amino acid capped nanocrystals

Organic crystals possess extremely large optical nonlinearity compared to inorganic crystals. Also organic compounds have the amenability for synthesis and scope for introducing desirable characteristics by inclusions. A wide variety of organic materials having electron donor and acceptor groups, generate high order of nonlinearity. In the present work, a new nonlinear optical crystal, L-citrulline oxalate (LCO) based on the aminoacid L-citrulline was grown using slow evaporation technique. Structural characterization was carried out by single crystal XRD. It crystallizes in the noncentrosymmetric, orthorhombic structure with space group P21 P21 P21. Functional groups present in the sample were identified by Fourier transform infra red (FTIR) and FT-Raman spectral analysis. On studying the FTIR and Raman spectra of the precursors L-citrulline and oxalic acid, used for growing L-citrulline oxalate crystal, it is found that the significant peaks of the precursors are present in the spectra of the L-citrulline oxalate crystal . This observation along with the presence of NH3 + group in the spectra of L-citrulline oxalate, confirms the formation of the charge transfer complex

Spectral and statistical characteristics of shoaling waves of Alleppey West coast of India

Some investigations on the spectral and statistical characteristics of deep water waves are available for Indian waters. But practically no systematic investigation on the shallow water wave spectral and probabilistic characteristics is made for any part of the Indian coast except for a few restricted studies. Hence a comprehensive study of the shallow water wave climate and their spectral and statistical characteristics for a location (Alleppey) along the southwest coast of India is undertaken based on recorded data. The results of the investigation are presented in this thesis.The thesis comprises of seven chapters

An adaptive cluster based routing scheme for mobile wireless sensor networks

Clustering schemes improve energy efficiency of wireless sensor networks. The inclusion of mobility as a new criterion for the cluster creation and maintenance adds new challenges for these clustering schemes. Cluster formation and cluster head selection is done on a stochastic basis for most of the algorithms. In this paper we introduce a cluster formation and routing algorithm based on a mobility factor. The proposed algorithm is compared with LEACH-M protocol based on metrics viz. number of cluster head transitions, average residual energy, number of alive nodes and number of messages lost

A Prototype for a Multimodal Biometric Security system based on Face and Audio Signatures

Any automatically measurable, robust and distinctive physical characteristic or personal trait that can be used to identify an individual or verify the claimed identity of an individual, referred to as biometrics, has gained significant interest in the wake of heightened concerns about security and rapid advancements in networking, communication and mobility. Multimodal biometrics is expected to be ultra-secure and reliable, due to the presence of multiple and independent—verification clues. In this study, a multimodal biometric system utilising audio and facial signatures has been implemented and error analysis has been carried out. A total of one thousand face images and 250 sound tracks of 50 users are used for training the proposed system. To account for the attempts of the unregistered signatures data of 25 new users are tested. The short term spectral features were extracted from the sound data and Vector Quantization was done using K-means algorithm. Face images are identified based on Eigen face approach using Principal Component Analysis. The success rate of multimodal system using speech and face is higher when compared to individual unimodal recognition systems

Energy Aware Cluster-based Multihop Routing Protocol for Sensor Networks

Clustering combined with multihop communication is a promising solution to cope with the energy requirements of large scale Wireless Sensor Networks. In this work, a new cluster based routing protocol referred to as Energy Aware Cluster-based Multihop (EACM) Routing Protocol is introduced, with multihop communication between cluster heads for transmitting messages to the base station and direct communication within clusters. We propose EACM with both static and dynamic clustering. The network is partitioned into near optimal load balanced clusters by using a voting technique, which ensures that the suitability of a node to become a cluster head is determined by all its neighbors. Results show that the new protocol performs better than LEACH on network lifetime and energy dissipation

Brain Tissue Classification from Multispectral MRI by Wavelet based Principal Component Analysis

In this paper, we propose a multispectral analysis system using wavelet based Principal Component Analysis (PCA), to improve the brain tissue classification from MRI images. Global transforms like PCA often neglects significant small abnormality details, while dealing with a massive amount of multispectral data. In order to resolve this issue, input dataset is expanded by detail coefficients from multisignal wavelet analysis. Then, PCA is applied on the new dataset to perform feature analysis. Finally, an unsupervised classification with Fuzzy C-Means clustering algorithm is used to measure the improvement in reproducibility and accuracy of the results. A detailed comparative analysis of classified tissues with those from conventional PCA is also carried out. Proposed method yielded good improvement in classification of small abnormalities with high sensitivity/accuracy values, 98.9/98.3, for clinical analysis. Experimental results from synthetic and clinical data recommend the new method as a promising approach in brain tissue analysis.

Wavelet based Independent Component Analysis for Multispectral Brain Tissue Classification

Multispectral analysis is a promising approach in tissue classification and abnormality detection from Magnetic Resonance (MR) images. But instability in accuracy and reproducibility of the classification results from conventional techniques keeps it far from clinical applications. Recent studies proposed Independent Component Analysis (ICA) as an effective method for source signals separation from multispectral MR data. However, it often fails to extract the local features like small abnormalities, especially from dependent real data. A multisignal wavelet analysis prior to ICA is proposed in this work to resolve these issues. Best de-correlated detail coefficients are combined with input images to give better classification results. Performance improvement of the proposed method over conventional ICA is effectively demonstrated by segmentation and classification using k-means clustering. Experimental results from synthetic and real data strongly confirm the positive effect of the new method with an improved Tanimoto index/Sensitivity values, 0.884/93.605, for reproduced small white matter lesions

Structural, topographical and magnetic evolution of RF-sputtered Fe-Ni alloy based thin films with thermal annealing

Metglas 2826 MB having a nominal composition of Fe40Ni38Mo4B18 is an excellent soft magnetic material and finds application in sensors and memory heads. However, the thin-film forms of Fe40Ni38Mo4B18 are seldom studied, although they are important in micro-electro-mechanical systems/nano-electromechanical systems devices. The stoichiometry of the film plays a vital role in determining the structural and magnetic properties of Fe40Ni38Mo4B18 thin films: retaining the composition in thin films is a challenge. Thin films of 52 nm thickness were fabricated by RF sputtering technique on silicon substrate from a target of nominal composition of Fe40Ni38Mo4B18. The films were annealed at temperatures of 400 °C and 600 °C. The micro-structural studies of films using glancing x-ray diffractometer (GXRD) and transmission electron microscope (TEM) revealed that pristine films are crystalline with (FeNiMo)23B6 phase. Atomic force microscope (AFM) images were subjected to power spectral density analysis to understand the probable surface evolution mechanism during sputtering and annealing. X-ray photoelectron spectroscopy (XPS) was employed to determine the film composition. The sluggish growth of crystallites with annealing is attributed to the presence of molybdenum in the thin film. The observed changes in magnetic properties were correlated with annealing induced structural, compositional and morphological changes

Development of Hierarchical Clustering Techniques for Gridded Data from Mixed Data Sequences

Knowledge discovery in databases is the non-trivial process of identifying valid, novel potentially useful and ultimately understandable patterns from data. The term Data mining refers to the process which does the exploratory analysis on the data and builds some model on the data. To infer patterns from data, data mining involves different approaches like association rule mining, classification techniques or clustering techniques. Among the many data mining techniques, clustering plays a major role, since it helps to group the related data for assessing properties and drawing conclusions. Most of the clustering algorithms act on a dataset with uniform format, since the similarity or dissimilarity between the data points is a significant factor in finding out the clusters. If a dataset consists of mixed attributes, i.e. a combination of numerical and categorical variables, a preferred approach is to convert different formats into a uniform format. The research study explores the various techniques to convert the mixed data sets to a numerical equivalent, so as to make it equipped for applying the statistical and similar algorithms. The results of clustering mixed category data after conversion to numeric data type have been demonstrated using a crime data set. The thesis also proposes an extension to the well known algorithm for handling mixed data types, to deal with data sets having only categorical data. The proposed conversion has been validated on a data set corresponding to breast cancer. Moreover, another issue with the clustering process is the visualization of output. Different geometric techniques like scatter plot, or projection plots are available, but none of the techniques display the result projecting the whole database but rather demonstrate attribute-pair wise analysis

Synthesis, spectral characterization and crystal structure of copper(II) complexes of 2-benzoylpyridine-N(4)-phenylsemicarbazone

An interesting series of nine new copper(II) complexes [Cu2L2(OAc)2] H2O (1), [CuLNCS] ½H2O (2), [CuLNO3] ½H2O (3), [Cu(HL)Cl2] H2O (4), [Cu2(HL)2(SO4)2] 4H2O (5), [CuLClO4] ½H2O (6), [CuLBr] 2H2O (7), [CuL2] H2O (8) and [CuLN3] CH3OH (9) of 2-benzoylpyridine-N(4)-phenyl semicarbazone (HL) have been synthesized and physico-chemically characterized. The tridentate character of the semicarbazone is inferred from IR spectra. Based on the EPR studies, spin Hamiltonian and bonding parameters have been calculated. The g values, calculated for all the complexes in frozen DMF, indicate the presence of the unpaired electron in the dx2 y2 orbital. The structure of the compound, [Cu2L2(OAc)2] (1a) has been resolved using single crystal X-ray diffraction studies. The crystal structure revealed monoclinic space group P21/n. The coordination geometry about the copper(II) in 1a is distorted square pyramidal with one pyridine nitrogen atom, the imino nitrogen, enolate oxygen and acetate oxygen in the basal plane, an acetate oxygen form adjacent moiety occupies the apical position, serving as a bridge to form a centrosymmetric dimeric structure

Air-gap based vertical cavity micro-opto-electro-mechanical Fabry-Perot filters

Mikrooptische Filter sind heutzutage in vielen Bereichen in der Telekommunikation unersetzlich. Wichtige Einsatzgebiete sind aber auch spektroskopische Systeme in der Medizin-, Prozess- und Umwelttechnik. Diese Arbeit befasst sich mit der Technologieentwicklung und Herstellung von luftspaltbasierenden, vertikal auf einem Substrat angeordneten, oberflächenmikromechanisch hergestellten Fabry-Perot-Filtern. Es werden zwei verschiedene Filtervarianten, basierend auf zwei verschiedenen Materialsystemen, ausführlich untersucht. Zum einen handelt es sich dabei um die Weiterentwicklung von kontinuierlich mikromechanisch durchstimmbaren InP / Luftspaltfiltern; zum anderen werden neuartige, kostengünstige Siliziumnitrid / Luftspaltfilter wissenschaftlich behandelt. Der Inhalt der Arbeit ist so gegliedert, dass nach einer Einleitung mit Vergleichen zu Arbeiten und Ergebnissen anderer Forschergruppen weltweit, zunächst einige theoretische Grundlagen zur Berechnung der spektralen Reflektivität und Transmission von beliebigen optischen Schichtanordnungen aufgezeigt werden. Auß erdem wird ein kurzer theoretischer Ü berblick zu wichtigen Eigenschaften von Fabry-Perot-Filtern sowie der Möglichkeit einer mikromechanischen Durchstimmbarkeit gegeben. Daran anschließ end folgt ein Kapitel, welches sich den grundlegenden technologischen Aspekten der Herstellung von luftspaltbasierenden Filtern widmet. Es wird ein Zusammenhang zu wichtigen Referenzarbeiten hergestellt, auf denen diverse Weiterentwicklungen dieser Arbeit basieren. Die beiden folgenden Kapitel erläutern dann ausführlich das Design, die Herstellung und die Charakterisierung der beiden oben erwähnten Filtervarianten. Abgesehen von der vorangehenden Epitaxie von InP / GaInAs Schichten, ist die Herstellung der InP / Luftspaltfilter komplett im Institut durchgeführt worden. Die Herstellungsschritte sind ausführlich in der Arbeit erläutert, wobei ein Schwerpunktthema das trockenchemische Ä tzen von InP sowie GaInAs, welches als Opferschichtmaterial für die Herstellung der Luftspalte genutzt wurde, behandelt. Im Verlauf der wissenschaftlichen Arbeit konnten sehr wichtige technische Verbesserungen entwickelt und eingesetzt werden, welche zu einer effizienteren technologischen Herstellung der Filter führten und in der vorliegenden Niederschrift ausführlich dokumentiert sind. Die hergestellten, für einen Einsatz in der optischen Telekommunikation entworfenen, elektrostatisch aktuierbaren Filter sind aus zwei luftspaltbasierenden Braggspiegeln aufgebaut, welche wiederum jeweils 3 InP-Schichten von (je nach Design) 357nm bzw. 367nm Dicke aufweisen. Die Filter bestehen aus im definierten Abstand parallel übereinander angeordneten Membranen, die über Verbindungsbrücken unterschiedlicher Anzahl und Länge an Haltepfosten befestigt sind. Da die mit 357nm bzw. 367nm vergleichsweise sehr dünnen Schichten freitragende Konstrukte mit bis zu 140 nm Länge bilden, aber trotzdem Positionsgenauigkeiten im nm-Bereich einhalten müssen, handelt es sich hierbei um sehr anspruchsvolle mikromechanische Bauelemente. Um den Einfluss der zahlreichen geometrischen Strukturparameter studieren zu können, wurden verschiedene laterale Filterdesigns implementiert. Mit den realisierten Filter konnte ein enorm weiter spektraler Abstimmbereich erzielt werden. Je nach lateralem Design wurden internationale Bestwerte für durchstimmbare Fabry-Perot-Filter von mehr als 140nm erreicht. Die Abstimmung konnte dabei kontinuierlich mit einer angelegten Spannung von nur wenigen Volt durchgeführt werden. Im Vergleich zu früher berichteten Ergebnissen konnten damit sowohl die Wellenlängenabstimmung als auch die dafür benötigte Abstimmungsspannung signifikant verbessert werden. Durch den hohen Brechungsindexkontrast und die geringe Schichtdicke zeigen die Filter ein vorteilhaftes, extrem weites Stopband in der Größ enordnung um 550nm. Die gewählten, sehr kurzen Kavitätslängen ermöglichen einen freien Spektralbereich des Filters welcher ebenfalls in diesen Größ enordnungen liegt, so dass ein weiter spektraler Einsatzbereich ermöglicht wird. Während der Arbeit zeigte sich, dass Verspannungen in den freitragenden InPSchichten die Funktionsweise der mikrooptischen Filter stark beeinflussen bzw. behindern. Insbesondere eine Unterätzung der Haltepfosten und die daraus resultierende Verbiegung der Ecken an denen sich die Verbindungsbrücken befinden, führte zu enormen vertikalen Membranverschiebungen, welche die Filtereigenschaften verändern. Um optimale Ergebnisse zu erreichen, muss eine weitere Verbesserung der Epitaxie erfolgen. Jedoch konnten durch den zusätzlichen Einsatz einer speziellen Schutzmaske die Unterätzung der Haltepfosten und damit starke vertikale Verformungen reduziert werden. Die aus der Verspannung resultierenden Verformungen und die Reaktion einzelner freistehender InP Schichten auf eine angelegte Gleich- oder Wechselspannung wurde detailliert untersucht. Mittels Weisslichtinterferometrie wurden lateral identische Strukturen verglichen, die aus unterschiedlich dicken InP-Schichten (357nm bzw. 1065nm) bestehen. Einen weiteren Hauptteil der Arbeit stellen Siliziumnitrid / Luftspaltfilter dar, welche auf einem neuen, im Rahmen dieser Dissertation entwickelten, technologischen Ansatz basieren. Die Filter bestehen aus zwei Braggspiegeln, die jeweils aus fünf 590nm dicken, freistehenden Siliziumnitridschichten aufgebaut sind und einem Abstand von 390nm untereinander aufweisen. Die Filter wurden auf Glassubstraten hergestellt. Der Herstellungsprozess ist jedoch auch mit vielen anderen Materialien oder Prozessen kompatibel, so dass z.B. eine Integration mit anderen Bauelemente relativ leicht möglich ist. Die Prozesse dieser ebenfalls oberflächenmikromechanisch hergestellten Filter wurden konsequent auf niedrige Herstellungskosten optimiert. Als Opferschichtmaterial wurde hier amorph abgeschiedenes Silizium verwendet. Der Herstellungsprozess beinhaltet die Abscheidung verspannungsoptimierter Schichten (Silizium und Siliziumnitrid) mittels PECVD, die laterale Strukturierung per reaktiven Ionenätzen mit den Gasen SF6 / CHF3 / Ar sowie Fotolack als Maske, die nasschemische Unterätzung der Opferschichten mittels KOH und das Kritisch-Punkt-Trocken der Proben. Die Ergebnisse der optischen Charakterisierung der Filter zeigen eine hohe Ü bereinstimmung zwischen den experimentell ermittelten Daten und den korrespondierenden theoretischen Modellrechnungen. Weisslichtinterferometermessungen der freigeätzten Strukturen zeigen ebene Filterschichten und bestätigen die hohe vertikale Positioniergenauigkeit, die mit diesem technologischen Ansatz erreicht werden kann.

Efficient data mining based on formal concept analysis

Formal Concept Analysis is an unsupervised learning technique for conceptual clustering. We introduce the notion of iceberg concept lattices and show their use in Knowledge Discovery in Databases (KDD). Iceberg lattices are designed for analyzing very large databases. In particular they serve as a condensed representation of frequent patterns as known from association rule mining. In order to show the interplay between Formal Concept Analysis and association rule mining, we discuss the algorithm TITANIC. We show that iceberg concept lattices are a starting point for computing condensed sets of association rules without loss of information, and are a visualization method for the resulting rules.

Model Calculations and Implementation of Filters and Hybrid Green VCSELs based on Optical Thin Film Stacks

This work introduced the novel conception of complex coupled hybrid VCSELs for the first time. Alternating organic and inorganic layers in the lasers provide periodic variation of refractive index and optical gain, which enable single mode operation and low threshold of the VCSELs. Model calculations revealed great reduction of the lasing threshold with factors over 30, in comparison with the existing micro-cavity lasers. Tunable green VCSEL has been also designed, implemented and analyzed taking advantage of the broad photoluminescence spectra of the organics. Free standing optical thin films without compressive stress are technologically implemented. Multiple membrane stacks with air gap in between have been fabricated for the implementation of complex coupled VCSEL structures. Complex coupled hybrid VCSEL is a very promising approach to fill the gaps in the green spectral range of the semiconductor lasers.

Optimization of the Mechanical and Optical Properties of Tunable Optical Sensor Arrays (TOSA) for a Nanospectrometer in the Visible and Near Infrared Spectral Range

Tunable Optical Sensor Arrays (TOSA) based on Fabry-Pérot (FP) filters, for high quality spectroscopic applications in the visible and near infrared spectral range are investigated within this work. The optical performance of the FP filters is improved by using ion beam sputtered niobium pentoxide (Nb2O5) and silicon dioxide (SiO2) Distributed Bragg Reflectors (DBRs) as mirrors. Due to their high refractive index contrast, only a few alternating pairs of Nb2O5 and SiO2 films can achieve DBRs with high reflectivity in a wide spectral range, while ion beam sputter deposition (IBSD) is utilized due to its ability to produce films with high optical purity. However, IBSD films are highly stressed; resulting in stress induced mirror curvature and suspension bending in the free standing filter suspensions of the MEMS (Micro-Electro-Mechanical Systems) FP filters. Stress induced mirror curvature results in filter transmission line degradation, while suspension bending results in high required filter tuning voltages. Moreover, stress induced suspension bending results in higher order mode filter operation which in turn degrades the optical resolution of the filter. Therefore, the deposition process is optimized to achieve both near zero absorption and low residual stress. High energy ion bombardment during film deposition is utilized to reduce the film density, and hence the film compressive stress. Utilizing this technique, the compressive stress of Nb2O5 is reduced by ~43%, while that for SiO2 is reduced by ~40%. Filters fabricated with stress reduced films show curvatures as low as 100 nm for 70 μm mirrors. To reduce the stress induced bending in the free standing filter suspensions, a stress optimized multi-layer suspension design is presented; with a tensile stressed metal sandwiched between two compressively stressed films. The stress in Physical Vapor Deposited (PVD) metals is therefore characterized for use as filter top-electrode and stress compensating layer. Surface micromachining is used to fabricate tunable FP filters in the visible spectral range using the above mentioned design. The upward bending of the suspensions is reduced from several micrometers to less than 100 nm and 250 nm for two different suspension layer combinations. Mechanical tuning of up to 188 nm is obtained by applying 40 V of actuation voltage. Alternatively, a filter line with transmission of 65.5%, Full Width at Half Maximum (FWHM) of 10.5 nm and a stopband of 170 nm (at an output wavelength of 594 nm) is achieved. Numerical model simulations are also performed to study the validity of the stress optimized suspension design for the near infrared spectral range, wherein membrane displacement and suspension deformation due to material residual stress is studied. Two bandpass filter designs based on quarter-wave and non-quarter-wave layers are presented as integral components of the TOSA. With a filter passband of 135 nm and a broad stopband of over 650 nm, high average filter transmission of 88% is achieved inside the passband, while maximum filter transmission of less than 1.6% outside the passband is achieved.

Uncertainty Propagation in Model-Based Recognition

Building robust recognition systems requires a careful understanding of the effects of error in sensed features. Error in these image features results in a region of uncertainty in the possible image location of each additional model feature. We present an accurate, analytic approximation for this uncertainty region when model poses are based on matching three image and model points, for both Gaussian and bounded error in the detection of image points, and for both scaled-orthographic and perspective projection models. This result applies to objects that are fully three- dimensional, where past results considered only two-dimensional objects. Further, we introduce a linear programming algorithm to compute the uncertainty region when poses are based on any number of initial matches. Finally, we use these results to extend, from two-dimensional to three- dimensional objects, robust implementations of alignmentt interpretation- tree search, and ransformation clustering.