A computer-algebraic approach to the study of the symmetry properties of molecules and clusters

This thesis work is dedicated to use the computer-algebraic approach for dealing with the group symmetries and studying the symmetry properties of molecules and clusters. The Maple package Bethe, created to extract and manipulate the group-theoretical data and to simplify some of the symmetry applications, is introduced. First of all the advantages of using Bethe to generate the group theoretical data are demonstrated. In the current version, the data of 72 frequently applied point groups can be used, together with the data for all of the corresponding double groups. The emphasize of this work is placed to the applications of this package in physics of molecules and clusters. Apart from the analysis of the spectral activity of molecules with point-group symmetry, it is demonstrated how Bethe can be used to understand the field splitting in crystals or to construct the corresponding wave functions. Several examples are worked out to display (some of) the present features of the Bethe program. While we cannot show all the details explicitly, these examples certainly demonstrate the great potential in applying computer algebraic techniques to study the symmetry properties of molecules and clusters. A special attention is placed in this thesis work on the flexibility of the Bethe package, which makes it possible to implement another applications of symmetry. This implementation is very reasonable, because some of the most complicated steps of the possible future applications are already realized within the Bethe. For instance, the vibrational coordinates in terms of the internal displacement vectors for the Wilson's method and the same coordinates in terms of cartesian displacement vectors as well as the Clebsch-Gordan coefficients for the Jahn-Teller problem are generated in the present version of the program. For the Jahn-Teller problem, moreover, use of the computer-algebraic tool seems to be even inevitable, because this problem demands an analytical access to the adiabatic potential and, therefore, can not be realized by the numerical algorithm. However, the ability of the Bethe package is not exhausted by applications, mentioned in this thesis work. There are various directions in which the Bethe program could be developed in the future. Apart from (i) studying of the magnetic properties of materials and (ii) optical transitions, interest can be pointed out for (iii) the vibronic spectroscopy, and many others. Implementation of these applications into the package can make Bethe a much more powerful tool.

A proposal for the diagnosis of uncertain dynamic systems based on interval models

The performance of a model-based diagnosis system could be affected by several uncertainty sources, such as,model errors,uncertainty in measurements, and disturbances. This uncertainty can be handled by mean of interval models.The aim of this thesis is to propose a methodology for fault detection, isolation and identification based on interval models. The methodology includes some algorithms to obtain in an automatic way the symbolic expression of the residual generators enhancing the structural isolability of the faults, in order to design the fault detection tests. These algorithms are based on the structural model of the system. The stages of fault detection, isolation, and identification are stated as constraint satisfaction problems in continuous domains and solved by means of interval based consistency techniques. The qualitative fault isolation is enhanced by a reasoning in which the signs of the symptoms are derived from analytical redundancy relations or bond graph models of the system. An initial and empirical analysis regarding the differences between interval-based and statistical-based techniques is presented in this thesis. The performance and efficiency of the contributions are illustrated through several application examples, covering different levels of complexity.

Design and evaluation of intelligent classifier based intrusion detection system

We have discovered a novel approach of intrusion detection system using an intelligent data classifier based on a self organizing map (SOM). We have surveyed all other unsupervised intrusion detection methods, different alternative SOM based techniques and KDD winner IDS methods. This paper provides a robust designed and implemented intelligent data classifier technique based on a single large size (30x30) self organizing map (SOM) having the capability to detect all types of attacks given in the DARPA Archive 1999 the lowest false positive rate being 0.04 % and higher detection rate being 99.73% tested using full KDD data sets and 89.54% comparable detection rate and 0.18% lowest false positive rate tested using corrected data sets.

Are you thinking what I’m thinking? Peer group similarities in adolescent hostile attribution tendencies

A bias towards attributing hostile intent to others has been linked to aggression. In an adolescent sample, we investigated whether peer group homophily exists in the tendency towards attributing hostile intent. We assessed hostile attribution tendencies and self-reported aggressive behaviours in a normative sample of 910 adolescents, and computed average peer group scores based on nominated friend scores. Results indicated that adolescents showed significant correlations between their own level of hostile attributions and that of their peer group. Further analyses indicated that this effect occurred specifically in reciprocal friendships, and was retained even once own and peer group level of aggression were controlled.

A new tetranuclear copper(II) complex with oximate bridges: structure, magnetic properties and DFT study

A new tetranuclear complex, [Cu4L4](ClO4)4·2H2O (1), has been synthesized from the self-assembly of copper(II) perchlorate and the tridentate Schiff base ligand (2E,3E)-3-(2-aminopropylimino) butan-2-one oxime (HL). Single-crystal X-ray diffraction studies reveal that complex 1 consists of a Cu4(NO)4 core where the four copper(II) centers having square pyramidal environment are arranged in a distorted tetrahedral geometry. They are linked together by a rare bridging mode (μ3-η1,η2,η1) of oximato ligands. Analysis of magnetic susceptibility data indicates moderate antiferromagnetic (J1 = −48 cm−1, J2 = −40 cm−1 and J3 = −52 cm−1) exchange interaction through σ-superexchange pathways (in-plane bridging) of the oxime group. Theoretical calculations based on DFT technique have been used to obtain the energy states of different spin configurations and estimate the coupling constants and to understand the exact magnetic exchange pathways.

The effect of carbonyl group in the asymmetry Of (3,4)J(CH) coupling constants in norbornanones

A rationalization of the known difference between the (3,4)J(C4H1) and (3,4)J(C1H4) couplings transmitted mainly through the 7-bridge in norbornanone is presented in terms of the effects of hyperconjugative interactions involving the carbonyl group. Theoretical and experimental studies Of (3,4)J(CH) couplings were carried out in 3-endo- and 3-exo-X-2-norbornanone derivatives (X = Cl, Br) and in exo- and endo-2-noborneol compounds. Hyperconjugative interactions were studied with the natural bond orbital (NBO) method. Hyperconjugative interactions involving the carbonyl pi*c(2) =o and sigma*c(2) =o antibonding orbitals produce a decrease of three-bond contribution to both (3,4) J(C4H1) and (3,4)J(C1H4) couplings. However, the latter antibonding orbital also undergoes a strong sigma c(3)-c(4) ->sigma*c(2) =o interaction, which defines an additional coupling pathway for (3,4)J(C4H1) but not for (3,4)J(C1H4). This pathway is similar to that known for homoallylic couplings, the only difference being the nature of the intermediate antibonding orbital; i.e. for (3,4)J(C4H1) it is of sigma*-type, while in homoallylic couplings it is of pi*-type. Copyright (c) 2007 John Wiley & Sons, Ltd.

Gas-Phase Nucleophilic and Elimination Reactions in Simple Alkyl Nitrates

There has been increasing interest in the gas-phase reactivity of alkyl nitrates because of their well-known applications as explosives and because of then role in atmospheric and in marine processes This manuscript describes an experimental study by FT-ICR techniques of the gas-phase reactions of OH(-) and F(-) with methyl and ethyl Innate For methyl nitrate, the main reaction channel is found to be an elimination process promoted by abstraction of an a proton from the methyl group. Nucleophilic displacement of nitrate anion through an S(N)2 process at the carbon center Is also found to he an important reaction channel with methyl nitrate In ethyl nitrate, Ruination of NO(3)(-) is greatly enhanced and this is attributed to the ease of an E2-type elimination process promoted by proton abstraction at the beta position of the ethyl group. Theoretical calculations at the MP2/6-311+G(3df,2p)//MP2/6-31+G(d) level of theory ale consistent with the relative importance of the reaction channels and suggest that these reactions proceed through a double well potential The calculations also predict that nucleophilic attack by OH(-) at the nitrogen center (Sn2@N) is energetically the rueful ad pathway but experiments with (18)OH(-) showed no evidence for this channel. Single-point calculations reveal a strong preference for approach to the emboli center and may explain the lack of reactivity at the nitrogen center. Calculations were also carried out or NH(2)(-) and SH(-) to establish the reactivity pattern to provide a better understanding of environmentally relevant nitrate esters.

ANALYSIS & STUDY OF AI TECHNIQUES FORAUTOMATIC CONDITION MONITORING OFRAILWAY TRACK INFRASTRUCTURE : Artificial Intelligence Techniques

Since the last decade the problem of surface inspection has been receiving great attention from the scientific community, the quality control and the maintenance of products are key points in several industrial applications.The railway associations spent much money to check the railway infrastructure. The railway infrastructure is a particular field in which the periodical surface inspection can help the operator to prevent critical situations. The maintenance and monitoring of this infrastructure is an important aspect for railway association.That is why the surface inspection of railway also makes importance to the railroad authority to investigate track components, identify problems and finding out the way that how to solve these problems. In railway industry, usually the problems find in railway sleepers, overhead, fastener, rail head, switching and crossing and in ballast section as well. In this thesis work, I have reviewed some research papers based on AI techniques together with NDT techniques which are able to collect data from the test object without making any damage. The research works which I have reviewed and demonstrated that by adopting the AI based system, it is almost possible to solve all the problems and this system is very much reliable and efficient for diagnose problems of this transportation domain. I have reviewed solutions provided by different companies based on AI techniques, their products and reviewed some white papers provided by some of those companies. AI based techniques likemachine vision, stereo vision, laser based techniques and neural network are used in most cases to solve the problems which are performed by the railway engineers.The problems in railway handled by the AI based techniques performed by NDT approach which is a very broad, interdisciplinary field that plays a critical role in assuring that structural components and systems perform their function in a reliable and cost effective fashion. The NDT approach ensures the uniformity, quality and serviceability of materials without causing any damage of that materials is being tested. This testing methods use some way to test product like, Visual and Optical testing, Radiography, Magnetic particle testing, Ultrasonic testing, Penetrate testing, electro mechanic testing and acoustic emission testing etc. The inspection procedure has done periodically because of better maintenance. This inspection procedure done by the railway engineers manually with the aid of AI based techniques.The main idea of thesis work is to demonstrate how the problems can be reduced of thistransportation area based on the works done by different researchers and companies. And I have also provided some ideas and comments according to those works and trying to provide some proposal to use better inspection method where it is needed.The scope of this thesis work is automatic interpretation of data from NDT, with the goal of detecting flaws accurately and efficiently. AI techniques such as neural networks, machine vision, knowledge-based systems and fuzzy logic were applied to a wide spectrum of problems in this area. Another scope is to provide an insight into possible research methods concerning railway sleeper, fastener, ballast and overhead inspection by automatic interpretation of data.In this thesis work, I have discussed about problems which are arise in railway sleepers,fastener, and overhead and ballasted track. For this reason I have reviewed some research papers related with these areas and demonstrated how their systems works and the results of those systems. After all the demonstrations were taking place of the advantages of using AI techniques in contrast with those manual systems exist previously.This work aims to summarize the findings of a large number of research papers deploying artificial intelligence (AI) techniques for the automatic interpretation of data from nondestructive testing (NDT). Problems in rail transport domain are mainly discussed in this work. The overall work of this paper goes to the inspection of railway sleepers, fastener, ballast and overhead.

New Insights on Nontechnical Losses Characterization Through Evolutionary-Based Feature Selection

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

A New Impedance Measurement System for PZT-Based Structural Health Monitoring

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

The Yang-Lee edge singularity in spin models on connected and non-connected rings

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Negative Even Grade mKdV Hierarchy and its Soliton Solutions

In this paper we discuss the algebraic construction of the mKdV hierarchy in terms of an affine Lie algebra (s) over capl(2). An interesting novelty araises from the negative even grade sector of the affine algebra leading to nonlinear integro-differential equations admiting non-trivial vacuum configuration. These solitons solutions are constructed systematically from generalization of the dressing method based on non zero vacua. The sub-hierarchies admiting such class of solutions are classified.

Symplectic actions on coadjoint orbits

We present a compact expression for the field theoretical actions based on the symplectic analysis of coadjoint orbits of Lie groups. The final formula for the action density α c becomes a bilinear form 〈(S, 1/λ), (y, m y)〉, where S is a 1-cocycle of the Lie group (a schwarzian type of derivative in conformai case), λ is a coefficient of the central element of the algebra and script Y sign ≡ (y, m y) is the generalized Maurer-Cartan form. In this way the action is fully determined in terms of the basic group theoretical objects. This result is illustrated on a number of examples, including the superconformal model with N = 2. In this case the method is applied to derive the N = 2 superspace generalization of the D=2 Polyakov (super-) gravity action in a manifest (2, 0) supersymmetric form. As a byproduct we also find a natural (2, 0) superspace generalization of the Beltrami equations for the (2, 0) supersymmetric world-sheet metric describing the transition from the conformal to the chiral gauge.

A graph-based framework for thermal faceprint characterization

Thermal faceprint has been paramount in the last years. Since we can handle with face recognition using images acquired in the infrared spectrum, an unique individual's signature can be obtained through the blood vessels network of the face. In this work, we propose a novel framework for thermal faceprint extraction using a collection of graph-based techniques, which were never used to this task up to date. A robust method of thermal face segmentation is also presented. The experiments, which were conducted over the UND Collection C dataset, have showed promising results. © 2011 Springer-Verlag.

Improving Parkinson's disease identification through evolutionary-based feature selection

Parkinson's disease (PD) automatic identification has been actively pursued over several works in the literature. In this paper, we deal with this problem by applying evolutionary-based techniques in order to find the subset of features that maximize the accuracy of the Optimum-Path Forest (OPF) classifier. The reason for the choice of this classifier relies on its fast training phase, given that each possible solution to be optimized is guided by the OPF accuracy. We also show results that improved other ones recently obtained in the context of PD automatic identification. © 2011 IEEE.