The Use of Data Envelopment Analysis as Equity Portfolio Selection Criterion in the Finnish Stock Market

This thesis examines the application of data envelopment analysis as an equity portfolio selection criterion in the Finnish stock market during period 2001-2011. A sample of publicly traded firms in the Helsinki Stock Exchange is examined in this thesis. The sample covers the majority of the publicly traded firms in the Helsinki Stock Exchange. Data envelopment analysis is used to determine the efficiency of firms using a set of input and output financial parameters. The set of financial parameters consist of asset utilization, liquidity, capital structure, growth, valuation and profitability measures. The firms are divided into artificial industry categories, because of the industry-specific nature of the input and output parameters. Comparable portfolios are formed inside the industry category according to the efficiency scores given by the DEA and the performance of the portfolios is evaluated with several measures. The empirical evidence of this thesis suggests that with certain limitations, data envelopment analysis can successfully be used as portfolio selection criterion in the Finnish stock market when the portfolios are rebalanced at annual frequency according to the efficiency scores given by the data envelopment analysis. However, when the portfolios were rebalanced every two or three years, the results are mixed and inconclusive.

Further analysis of open-respirometry systems: an a-compartmental mechanistic approach

A system is said to be "instantaneous" when for a given constant input an equilibrium output is obtained after a while. In the meantime, the output is changing from its initial value towards the equilibrium one. This is the transient period of the system and transients are important features of open-respirometry systems. During transients, one cannot compute the input amplitude directly from the output. The existing models (e.g., first or second order dynamics) cannot account for many of the features observed in real open-respirometry systems, such as time lag. Also, these models do not explain what should be expected when a system is speeded up or slowed down. The purpose of the present study was to develop a mechanistic approach to the dynamics of open-respirometry systems, employing basic thermodynamic concepts. It is demonstrated that all the main relevant features of the output dynamics are due to and can be adequately explained by a distribution of apparent velocities within the set of molecules travelling along the system. The importance of the rate at which the molecules leave the sensor is explored for the first time. The study approaches the difference in calibrating a system with a continuous input and with a "unit impulse": the former truly reveals the dynamics of the system while the latter represents the first derivative (in time) of the former and, thus, cannot adequately be employed in the apparent time-constant determination. Also, we demonstrate why the apparent order of the output changes with volume or flow.

Energy and raw material consumption analysis of powder bed fusion: case study: CNC machining and laser additive manufacturing

Laser additive manufacturing (LAM), known also as 3D printing, is a powder bed fusion (PBF) type of additive manufacturing (AM) technology used to manufacture metal parts layer by layer by assist of laser beam. The development of the technology from building just prototype parts to functional parts is due to design flexibility. And also possibility to manufacture tailored and optimised components in terms of performance and strength to weight ratio of final parts. The study of energy and raw material consumption in LAM is essential as it might facilitate the adoption and usage of the technique in manufacturing industries. The objective this thesis was find the impact of LAM on environmental and economic aspects and to conduct life cycle inventory of CNC machining and LAM in terms of energy and raw material consumption at production phases. Literature overview in this thesis include sustainability issues in manufacturing industries with focus on environmental and economic aspects. Also life cycle assessment and its applicability in manufacturing industry were studied. UPLCI-CO2PE! Initiative was identified as mostly applied exiting methodology to conduct LCI analysis in discrete manufacturing process like LAM. Many of the reviewed literature had focused to PBF of polymeric material and only few had considered metallic materials. The studies that had included metallic materials had only measured input and output energy or materials of the process and compared to different AM systems without comparing to any competitive process. Neither did any include effect of process variation when building metallic parts with LAM. Experimental testing were carried out to make dissimilar samples with CNC machining and LAM in this thesis. Test samples were designed to include part complexity and weight reductions. PUMA 2500Y lathe machine was used in the CNC machining whereas a modified research machine representing EOSINT M-series was used for the LAM. The raw material used for making the test pieces were stainless steel 316L bar (CNC machined parts) and stainless steel 316L powder (LAM built parts). An analysis of power, time, and the energy consumed in each of the manufacturing processes on production phase showed that LAM utilises more energy than CNC machining. The high energy consumption was as result of duration of production. Energy consumption profiles in CNC machining showed fluctuations with high and low power ranges. LAM energy usage within specific mode (standby, heating, process, sawing) remained relatively constant through the production. CNC machining was limited in terms of manufacturing freedom as it was not possible to manufacture all the designed sample by machining. And the one which was possible was aided with large amount of material removed as waste. Planning phase in LAM was shorter than in CNC machining as the latter required many preparation steps. Specific energy consumption (SEC) were estimated in LAM based on the practical results and assumed platform utilisation. The estimated platform utilisation showed SEC could reduce when more parts were placed in one build than it was in with the empirical results in this thesis (six parts).

AnaBench: a Web/CORBA-based workbench for biomolecular sequence analysis

Affiliation: Département de biochimie, Faculté de médecine, Université de Montréal

Analysis and Design of an Adaptive Polynomial Predistorter with the Loop Delay Estimator

Most adaptive linearization circuits for the nonlinear amplifier have a feedback loop that returns the output signal oj'tne eunplifier to the lineurizer. The loop delay of the linearizer most be controlled precisely so that the convergence of the linearizer should be assured lot this Letter a delay control circuit is presented. It is a delay lock loop (ULL) with it modified early-lute gate and can he easily applied to a DSP implementation. The proposed DLL circuit is applied to an adaptive linearizer with the use of a polynomial predistorter, and the simulalion for a 16-QAM signal is performed. The simulation results show that the proposed DLL eliminates the delay between the reference input signal and the delayed feedback signal of the linearizing circuit perfectly, so that the predistorter polynomial coefficients converge into the optimum value and a high degree of linearization is achieved

Movement of Input and Output Prices of Rice in Kerala and its Impact on Area, Yield and Outp

Rice is the most extensively cultivated crop in the world, particularly concentrated in Asia and the Far East. Asian countries together make up for as much as 91.80 per cent of the world production of rice in 1986. The main objective of the present study is to analyse the rice economy of Kerala over time and space at the State, district and taluk level. The thesis analyses the trends in area, yield and total production of rice during the three seasons in the state, districts and taluks and studies the trends in input and output prices of rice and coconut in the state, districts and taluks. The researcher estimates the impact of input and output prices on area, yield and total output of rice in the state, districts and selected taluks and examines the conversion of paddy field into coconut garden and rubber plantation.

Example Based Image Analysis and Synthesis

Image analysis and graphics synthesis can be achieved with learning techniques using directly image examples without physically-based, 3D models. In our technique: -- the mapping from novel images to a vector of "pose" and "expression" parameters can be learned from a small set of example images using a function approximation technique that we call an analysis network; -- the inverse mapping from input "pose" and "expression" parameters to output images can be synthesized from a small set of example images and used to produce new images using a similar synthesis network. The techniques described here have several applications in computer graphics, special effects, interactive multimedia and very low bandwidth teleconferencing.

Sistema de información geográfica para web con informaciones espaciales (geográficas) de output y input para expediciones

This project is a Web Geographic Information System built on an Open Source geographic structure like MapServer (Minnesota University) and PostgreSQL/PostGIS (object relational database management system). The study case is a web site for expeditions in a specific Brazilian region

Input and output modality effects in immediate serial recall

In immediate recall tasks, visual recency is substantially enhanced when output interference is low (Cowan, Saults, Elliott, & Moreno, 2002; Craik, 1969) whereas auditory recency remains high even under conditions of high output interference. Ibis auditory advantage has been interpreted in terms of auditory resistance to output interference (e.g., Neath & Surprenant, 2003). In this study the auditory-visual difference at low output interference re-emerged when ceiling effects were accounted for, but only with spoken output. With written responding the auditory advantage remained significantly larger with high than with low output interference. These new data suggest that both superior auditory encoding and modality-specific output interference contribute to the classic auditory-visual modality effect.

Design of a minimum variance multiple input-multiple output neuro self-tuning proportional-integral-derivative controller for non-linear dynamic systems

In this study a minimum variance neuro self-tuning proportional-integral-derivative (PID) controller is designed for complex multiple input-multiple output (MIMO) dynamic systems. An approximation model is constructed, which consists of two functional blocks. The first block uses a linear submodel to approximate dominant system dynamics around a selected number of operating points. The second block is used as an error agent, implemented by a neural network, to accommodate the inaccuracy possibly introduced by the linear submodel approximation, various complexities/uncertainties, and complicated coupling effects frequently exhibited in non-linear MIMO dynamic systems. With the proposed model structure, controller design of an MIMO plant with n inputs and n outputs could be, for example, decomposed into n independent single input-single output (SISO) subsystem designs. The effectiveness of the controller design procedure is initially verified through simulations of industrial examples.

Performance analysis of the LMS blind minimum-output-energy CDMA detector

Adaptive filters used in code division multiple access (CDMA) receivers to counter interference have been formulated both with and without the assumption of training symbols being transmitted. They are known as training-based and blind detectors respectively. We show that the convergence behaviour of the blind minimum-output-energy (MOE) detector can be quite easily derived, unlike what was implied by the procedure outlined in a previous paper. The simplification results from the observation that the correlation matrix determining convergence performance can be made symmetric, after which many standard results from the literature on least mean square (LMS) filters apply immediately.

Using meteorological wind data to estimate turbine generation output: a sensitivity analysis

Various studies investigating the future impacts of integrating high levels of renewable energy make use of historical meteorological (met) station data to produce estimates of future generation. Hourly means of 10m horizontal wind are extrapolated to a standard turbine hub height using the wind profile power or log law and used to simulate the hypothetical power output of a turbine at that location; repeating this procedure using many viable locations can produce a picture of future electricity generation. However, the estimate of hub height wind speed is dependent on the choice of the wind shear exponent a or the roughness length z0, and requires a number of simplifying assumptions. This paper investigates the sensitivity of this estimation on generation output using a case study of a met station in West Freugh, Scotland. The results show that the choice of wind shear exponent is a particularly sensitive parameter which can lead to significant variation of estimated hub height wind speed and hence estimated future generation potential of a region.