Railways, Airports and Sea Container Operators as Publicly Listed Companies – Financial Performance and Shareholder Value Creation Perspective

Logistics infrastructure and transportation services have been the liability of countries and governments for decades, or these have been under strict regulation policies. One of the first branches opened for competition in EU as well as in other continents, has been air transports (operators, like passenger and freight) and road transports. These have resulted on lower costs, better connectivity and in most of the cases higher service quality. However, quite large amount of other logistics related activities are still directly (or indirectly) under governmental influence, e.g. railway infrastructure, road infrastructure, railway operations, airports, and sea ports. Due to the globalization, governmental influence is not that necessary in this sector, since transportation needs have increased with much more significant phase as compared to economic growth. Also freight transportation needs do not correlate with passenger side, due to the reason that only small number of areas in the world have specialized in the production of particular goods. Therefore, in number of cases public-private partnership, or even privately owned companies operating in these sub-branches have been identified as beneficial for countries, customers and further economic growth. The objective of this research work is to shed more light on these kinds of experiments, especially in the relatively unknown sub-branches of logistics like railways, airports and sea container transports. In this research work we have selected companies having public listed status in some stock exchange, and have needed amount of financial scale to be considered as serious company rather than start-up phase venture. Our research results show that railways and airports usually need high fixed investments, but have showed in the last five years generally good financial performance, both in terms of profitability and cash flow. In contrary to common belief of prosperity in globally growing container transports, sea vessel operators of containers have not shown that impressive financial performance. Generally margins in this business are thin, and profitability has been sacrificed in front of high growth – this also concerns cash flow performance, which has been lower too. However, as we examine these three logistics sub-branches through shareholder value development angle during time period of 2002-2007, we were surprised to find out that all of these three have outperformed general stock market indexes in this period. More surprising is the result that financially a bit less performing sea container transportation sector shows highest shareholder value gain in the examination period. Thus, it should be remembered that provided analysis shows only limited picture, since e.g. dividends were not taken into consideration in this research work. Therefore, e.g. US railway operators have disadvantage to other in the analysis, since they have been able to provide dividends for shareholders in long period of time. Based on this research work we argue that investment on transportation/logistics sector seems to be safe alternative, which yields with relatively low risk high gain. Although global economy would face smaller growth period, this sector seems to provide opportunities in more demanding situation as well.

Fuzzy tolerance/equivalence relations from intersection, union and complement operators and their application to a clustering method

This master thesis work introduces the fuzzy tolerance/equivalence relation and its application in cluster analysis. The work presents about the construction of fuzzy equivalence relations using increasing generators. Here, we investigate and research on the role of increasing generators for the creation of intersection, union and complement operators. The objective is to develop different varieties of fuzzy tolerance/equivalence relations using different varieties of increasing generators. At last, we perform a comparative study with these developed varieties of fuzzy tolerance/equivalence relations in their application to a clustering method.

Differential evolution based classification with pool of distances and aggregation operators

The objective of this thesis is to develop and generalize further the differential evolution based data classification method. For many years, evolutionary algorithms have been successfully applied to many classification tasks. Evolution algorithms are population based, stochastic search algorithms that mimic natural selection and genetics. Differential evolution is an evolutionary algorithm that has gained popularity because of its simplicity and good observed performance. In this thesis a differential evolution classifier with pool of distances is proposed, demonstrated and initially evaluated. The differential evolution classifier is a nearest prototype vector based classifier that applies a global optimization algorithm, differential evolution, to determine the optimal values for all free parameters of the classifier model during the training phase of the classifier. The differential evolution classifier applies the individually optimized distance measure for each new data set to be classified is generalized to cover a pool of distances. Instead of optimizing a single distance measure for the given data set, the selection of the optimal distance measure from a predefined pool of alternative measures is attempted systematically and automatically. Furthermore, instead of only selecting the optimal distance measure from a set of alternatives, an attempt is made to optimize the values of the possible control parameters related with the selected distance measure. Specifically, a pool of alternative distance measures is first created and then the differential evolution algorithm is applied to select the optimal distance measure that yields the highest classification accuracy with the current data. After determining the optimal distance measures for the given data set together with their optimal parameters, all determined distance measures are aggregated to form a single total distance measure. The total distance measure is applied to the final classification decisions. The actual classification process is still based on the nearest prototype vector principle; a sample belongs to the class represented by the nearest prototype vector when measured with the optimized total distance measure. During the training process the differential evolution algorithm determines the optimal class vectors, selects optimal distance metrics, and determines the optimal values for the free parameters of each selected distance measure. The results obtained with the above method confirm that the choice of distance measure is one of the most crucial factors for obtaining higher classification accuracy. The results also demonstrate that it is possible to build a classifier that is able to select the optimal distance measure for the given data set automatically and systematically. After finding optimal distance measures together with optimal parameters from the particular distance measure results are then aggregated to form a total distance, which will be used to form the deviation between the class vectors and samples and thus classify the samples. This thesis also discusses two types of aggregation operators, namely, ordered weighted averaging (OWA) based multi-distances and generalized ordered weighted averaging (GOWA). These aggregation operators were applied in this work to the aggregation of the normalized distance values. The results demonstrate that a proper combination of aggregation operator and weight generation scheme play an important role in obtaining good classification accuracy. The main outcomes of the work are the six new generalized versions of previous method called differential evolution classifier. All these DE classifier demonstrated good results in the classification tasks.

Agonistic-like responses from the torus semicircularis dorsalis elicited by GABA A blockade in the weakly electric fish Gymnotus carapo

Findings by our group have shown that the dorsolateral telencephalon of Gymnotus carapo sends efferents to the mesencephalic torus semicircularis dorsalis (TSd) and that presumably this connection is involved in the changes in electric organ discharge (EOD) and in skeletomotor responses observed following microinjections of GABA A antagonist bicuculline into this telencephalic region. Other studies have implicated the TSd or its mammalian homologue, the inferior colliculus, in defensive responses. In the present study, we explore the possible involvement of the TSd and of the GABA-ergic system in the modulation of the electric and skeletomotor displays. For this purpose, different doses of bicuculline (0.98, 0.49, 0.245, and 0.015 mM) and muscimol (15.35 mM) were microinjected (0.1 µL) in the TSd of the awake G. carapo. Microinjection of bicuculline induced dose-dependent interruptions of EOD and increased skeletomotor activity resembling defense displays. The effects of the two highest doses showed maximum values at 5 min (4.3 ± 2.7 and 3.8 ± 2.0 Hz, P < 0.05) and persisted until 10 min (11 ± 5.7 and 8.7 ± 5.2 Hz, P < 0.05). Microinjections of muscimol were ineffective. During the interruptions of EOD, the novelty response (increased frequency in response to sensory novelties) induced by an electric stimulus delivered by a pair of electrodes placed in the water of the experimental cuvette was reduced or abolished. These data suggest that the GABA-ergic mechanisms of the TSd inhibit the neural substrate of the defense reaction at this midbrain level.

Omnibus accounts to Finnish investors? – An analysis of the costs and benefits that omnibus account structure brings to Finnish account operators and investors

The Finnish Securities Markets are being harmonized to enable better, more reliable and timely settlement of securities. Omnibus accounts are a common practice in the European securities markets. Finland forbids the use of omnibus accounts from its domestic investors. There is a possibility that the omnibus account usage is allowed for Finnish investors in the future. This study aims to build a comprehensive image to Finnish investors and account operators in determining the costs and benefits that the omnibus account structure would have for them. This study uses qualitative research methods. A literature review provides the framework for this study. Different kinds of research articles, regulatory documents, studies performed by European organisations, and Finnish news reportages are used to analyse the costs and benefits of omnibus accounts. The viewpoint is strictly of account operators and investors, and different effects on them are contemplated. The results of the analysis show that there are a number of costs and benefits that investors and account operators must take into consideration regarding omnibus accounts. The costs are related to development of IT-systems so that participants are able to adapt to the new structure and operate according to its needs. Decrease in the holdings’ transparency is a disadvantage of the structure and needs to be assessed precisely to avoid some problems it might bring. Benefits are mostly related to the increased competition in the securities markets as well as to the possible cost reductions of securities settlement. The costs and benefits were analysed according to the study plan of this thesis and as a result, the significance and impact of omnibus accounts to Finnish investors and account operators depends on the competition level and the decisions that all market participants make when determining if the account structure is beneficial for their operations.

ON APPROXIMATION METHODS FOR UNBOUNDED OPERATORS

Department of Mathematics, Cochin University of Science and Technology

Studies on some graph operators and related topics

Department of Mathematics, Cochin University of Science and Technology

A Study of Elementary Operators

Department of Mathematics, Cochin University of Science and Technology

Spectral Analysis of Bounded Self-adjoint operators - A Linear Algebraic Approach

This thesis Entitled Spectral theory of bounded self-adjoint operators -A linear algebraic approach.The main results of the thesis can be classified as three different approaches to the spectral approximation problems. The truncation method and its perturbed versions are part of the classical linear algebraic approach to the subject. The usage of block Toeplitz-Laurent operators and the matrix valued symbols is considered as a particular example where the linear algebraic techniques are effective in simplifying problems in inverse spectral theory. The abstract approach to the spectral approximation problems via pre-conditioners and Korovkin-type theorems is an attempt to make the computations involved, well conditioned. However, in all these approaches, linear algebra comes as the central object. The objective of this study is to discuss the linear algebraic techniques in the spectral theory of bounded self-adjoint operators on a separable Hilbert space. The usage of truncation method in approximating the bounds of essential spectrum and the discrete spectral values outside these bounds is well known. The spectral gap prediction and related results was proved in the second chapter. The discrete versions of Borg-type theorems, proved in the third chapter, partly overlap with some known results in operator theory. The pure linear algebraic approach is the main novelty of the results proved here.

A Study of Morphological Operators with Applications

The present work deals with the A study of morphological opertors with applications. Morphology is now a.necessary tool for engineers involved with imaging applications. Morphological operations have been viewed as filters the properties of which have been well studied (Heijmans, 1994). Another well-known class of non-linear filters is the class of rank order filters (Pitas and Venetsanopoulos, 1990). Soft morphological filters are a combination of morphological and weighted rank order filters (Koskinen, et al., 1991, Kuosmanen and Astola, 1995). They have been introduced to improve the behaviour of traditional morphological filters in noisy environments. The idea was to slightly relax the typical morphological definitions in such a way that a degree of robustness is achieved, while most of the desirable properties of typical morphological operations are maintained. Soft morphological filters are less sensitive to additive noise and to small variations in object shape than typical morphological filters. They can remove positive and negative impulse noise, preserving at the same time small details in images. Currently, Mathematical Morphology allows processing images to enhance fuzzy areas, segment objects, detect edges and analyze structures. The techniques developed for binary images are a major step forward in the application of this theory to gray level images. One of these techniques is based on fuzzy logic and on the theory of fuzzy sets.Fuzzy sets have proved to be strongly advantageous when representing in accuracies, not only regarding the spatial localization of objects in an image but also the membership of a certain pixel to a given class. Such inaccuracies are inherent to real images either because of the presence of indefinite limits between the structures or objects to be segmented within the image due to noisy acquisitions or directly because they are inherent to the image formation methods.