Valkolakki vai haalarit, vaiko molemmat : Koulutuspolitiikan vaikuttajien näkemykset toisen asteen kehityksestä

In the present research Finnish education policy-makers describe the transformation in upper secondary education in the 1990s. They answered questions related to equality and all-round education. The timeline of the research extends from the early development of the welfare state and equality policy to the 2000s. Its focus is on upper secondary education, which, in this paper, denotes general upper secondary education and vocational upper secondary education. The chronological analysis proceeds from the education committee of 1971 up to the youth education experiment of the 1990s. The voices of the then policy-makers are heard in this research. They were the ones who planned the reforms and/or made the decisions. This being the case, the interviewees include cabinet ministers, permanent secretaries, representatives of organisations and the research community as well as civil servants. The research material can be construed as contextual interpretations of the past, influenced by both the times and places where the narrations were given. The persons interviewed described their experiences and views on education policy. In their narratives they illustrated the transformation that occurred in relation to equality and all-round education. The narrative interviews painted a picture of the upper secondary education transformation and the matriculation examination as having a slowing effect on education policy reforms. It was not until the 1990s when the said examination began to make a difference to students in vocational upper secondary education Those interviewed named the persons who, in their opinion, had the most say in Finnish education policy. This list comprised a small circle of people who more or less agreed on the grand values of education policy, i.e. all-round education and equality. Only a small minority represented a radical view of equality, being true believers in universal upper secondary education implemented in accordance with comprehensive school reform. Finnish education policy was led from the perspective of traditional conception of equality from the 1970s to the 1980s. The transformation finally occurred in the 1990s when equality was understood to mean individual needs and the right to choose. As was the case with matriculation education, the insistence on all-round education also hampered the development of universal upper secondary education. The interviews revealed that any attempts to increase the academic syllabus of vocational education caused organisations as well as other policy-makers to oppose such development well into the 1980s. It was not until the youth education experiment of the 1990s that vocational education finally carved a path to higher education, when the polytechnic schools were made permanent. Three principal groups of key players emerged in the research: ministers of education, civil servants and organisations. The research showed that the ministers and civil servant education policy-makers of the 1990s also included only handful women. The circle of policy-makers was small and represented similar schools of thought. In the 1970s era of government committees, representatives of organisations actively participated in education policy. When the committee establishment was discontinued, this eliminated lobbying venues for the organisations. Nonetheless, the organisations regained their policymaking status in the 1990s. New lobbying organisations included the Finnish Entrepreneurs and the Union of Finnish Upper Secondary School Students. However, in contrast to the 1970s, only rarely would individuals rise from the ranks of organisations to the cadre of policy-makers. The interviewees had a twofold view of neo-liberalism Contrary to other policy-makers, representatives of the research community and organisations concur that neo-liberalism did exist in education policy decision-making in the 1990s.

Individuals' Responsibility in Corporations

I discuss role responsibly, individual responsibility and collective responsibility in corporate multinational setting. My case study is about minerals used in electronics that come from the Democratic Republic of Congo. What I try to show throughout the thesis is how many things need to be taken into consideration when we discuss the responsibility of individuals in corporations. No easy and simple answers are available. Instead, we must keep in mind the complexity of the situation at all times, judging cases on individual basis, emphasizing the importance of individual judgement and virtue, as well as the responsibility we all share as members of groups and the wider society. I begin by discussing the demands that are placed on us as employees. There is always a potential for a conflict between our different roles and also the wider demands placed on us. Role demands are usually much more specific than the wider question of how we should act as human beings. The terminology of roles can also be misleading as it can create illusions about our work selves being somehow radically separated from our everyday, true selves. The nature of collective decision-making and its implications for responsibility is important too. When discussing the moral responsibility of an employee in a corporate setting, one must take into account arguments from individual and collective responsibility, as well as role ethics. Individual responsibility is not a separate or competing notion from that of collective responsibility. Rather, the two are interlinked. Individuals' responsibilities in collective settings combine both individual responsibility and collective responsibility (which is different from aggregate individual responsibility). In the majority of cases, both will apply in various degrees. Some members might have individual responsibility in addition to the collective responsibility, while others just the collective responsibility. There are also times when no-one bears individual moral responsibility but the members are still responsible for the collective part. My intuition is that collective moral responsibility is strongly linked to the way the collective setting affects individual judgements and moulds the decisions, and how the individuals use the collective setting to further their own ends. Individuals remain the moral agents but responsibility is collective if the actions in question are collective in character. I also explore the impacts of bureaucratic ethic and its influence on the individual. Bureaucracies can compartmentalize work to such a degree that individual human action is reduced to mere behaviour. Responsibility is diffused and the people working in the bureaucracy can come to view their actions to be outside the normal human realm where they would be responsible for what they do. Language games and rules, anonymity, internal power struggles, and the fragmentation of information are just some of the reasons responsibility and morality can get blurry in big institutional settings. Throughout the thesis I defend the following theses: ● People act differently depending on their roles. This is necessary for our society to function, but the more specific role demands should always be kept in check by the wider requirements of being a good human being. ● Acts in corporations (and other large collectives) are not reducible to individual actions, and cannot be explained fully by the behaviour of individual employees. ● Individuals are responsible for the actions that they undertake in the collective as role occupiers and are very rarely off the hook. Hiding behind role demands is usually only an excuse and shows a lack of virtue. ● Individuals in roles can be responsible even when the collective is not. This depends on if the act they performed was corporate in nature or not. ● Bureaucratic structure affects individual thinking and is not always a healthy environment to work in. ● Individual members can share responsibility with the collective and our share of the collective responsibility is strongly linked to our relations. ● Corporations and other collectives can be responsible for harm even when no individual is at fault. The structure and the policies of the collective are crucial. ● Socialization plays an important role in our morality at both work and outside it. We are all responsible for the kind of moral context we create. ● When accepting a role or a position in a collective, we are attaching ourselves with the values of that collective. ● Ethical theories should put more emphasis on good judgement and decision-making instead of vague generalisations. My conclusion is that the individual person is always in the centre when it comes to responsibility, and not so easily off the hook as we sometimes think. What we do, and especially who we choose to associate ourselves with, does matter and we should be more careful when we choose who we work for. Individuals within corporations are responsible for choosing that the corporation they associate with is one that they can ascribe to morally, if not fully, then at least for the most part. Individuals are also inclusively responsible to a varying degree for the collective activities they contribute to, even in overdetermined contexts. We all are responsible for the kind of corporations we choose to support through our actions as consumers, investors and citizens.

Search for the Higgs boson in the all-hadronic final state using the CDF II detector

We report on a search for the production of the Higgs boson decaying to two bottom quarks accompanied by two additional quarks. The data sample used corresponds to an integrated luminosity of approximately 4  fb-1 of pp̅ collisions at √s=1.96  TeV recorded by the CDF II experiment. This search includes twice the integrated luminosity of the previous published result, uses analysis techniques to distinguish jets originating from light flavor quarks and those from gluon radiation, and adds sensitivity to a Higgs boson produced by vector boson fusion. We find no evidence of the Higgs boson and place limits on the Higgs boson production cross section for Higgs boson masses between 100  GeV/c2 and 150  GeV/c2 at the 95% confidence level. For a Higgs boson mass of 120  GeV/c2, the observed (expected) limit is 10.5 (20.0) times the predicted standard model cross section.

Locally checkable proofs

This work studies decision problems from the perspective of nondeterministic distributed algorithms. For a yes-instance there must exist a proof that can be verified with a distributed algorithm: all nodes must accept a valid proof, and at least one node must reject an invalid proof. We focus on locally checkable proofs that can be verified with a constant-time distributed algorithm. For example, it is easy to prove that a graph is bipartite: the locally checkable proof gives a 2-colouring of the graph, which only takes 1 bit per node. However, it is more difficult to prove that a graph is not bipartite—it turns out that any locally checkable proof requires Ω(log n) bits per node. In this work we classify graph problems according to their local proof complexity, i.e., how many bits per node are needed in a locally checkable proof. We establish tight or near-tight results for classical graph properties such as the chromatic number. We show that the proof complexities form a natural hierarchy of complexity classes: for many classical graph problems, the proof complexity is either 0, Θ(1), Θ(log n), or poly(n) bits per node. Among the most difficult graph properties are symmetric graphs, which require Ω(n2) bits per node, and non-3-colourable graphs, which require Ω(n2/log n) bits per node—any pure graph property admits a trivial proof of size O(n2).

An actor-critic algorithm with function approximation for discounted cost constrained Markov decision processes

We develop in this article the first actor-critic reinforcement learning algorithm with function approximation for a problem of control under multiple inequality constraints. We consider the infinite horizon discounted cost framework in which both the objective and the constraint functions are suitable expected policy-dependent discounted sums of certain sample path functions. We apply the Lagrange multiplier method to handle the inequality constraints. Our algorithm makes use of multi-timescale stochastic approximation and incorporates a temporal difference (TD) critic and an actor that makes a gradient search in the space of policy parameters using efficient simultaneous perturbation stochastic approximation (SPSA) gradient estimates. We prove the asymptotic almost sure convergence of our algorithm to a locally optimal policy. (C) 2010 Elsevier B.V. All rights reserved.

Mining Land Cover Information Using Multilayer Perceptron and Decision Tree from MODIS Data

Land cover (LC) changes play a major role in global as well as at regional scale patterns of the climate and biogeochemistry of the Earth system. LC information presents critical insights in understanding of Earth surface phenomena, particularly useful when obtained synoptically from remote sensing data. However, for developing countries and those with large geographical extent, regular LC mapping is prohibitive with data from commercial sensors (high cost factor) of limited spatial coverage (low temporal resolution and band swath). In this context, free MODIS data with good spectro-temporal resolution meet the purpose. LC mapping from these data has continuously evolved with advances in classification algorithms. This paper presents a comparative study of two robust data mining techniques, the multilayer perceptron (MLP) and decision tree (DT) on different products of MODIS data corresponding to Kolar district, Karnataka, India. The MODIS classified images when compared at three different spatial scales (at district level, taluk level and pixel level) shows that MLP based classification on minimum noise fraction components on MODIS 36 bands provide the most accurate LC mapping with 86% accuracy, while DT on MODIS 36 bands principal components leads to less accurate classification (69%).

Towards building an intelligent decision support system for project management

Management of large projects, especially the ones in which a major component of R&D is involved and those requiring knowledge from diverse specialised and sophisticated fields, may be classified as semi-structured problems. In these problems, there is some knowledge about the nature of the work involved, but there are also uncertainties associated with emerging technologies. In order to draw up a plan and schedule of activities of such a large and complex project, the project manager is faced with a host of complex decisions that he has to take, such as, when to start an activity, for how long the activity is likely to continue, etc. An Intelligent Decision Support System (IDSS) which aids the manager in decision making and drawing up a feasible schedule of activities while taking into consideration the constraints of resources and time, will have a considerable impact on the efficient management of the project. This report discusses the design of an IDSS that helps in project planning phase through the scheduling phase. The IDSS uses a new project scheduling tool, the Project Influence Graph (PIG).

WEPA: Wind energy potential assessment-spatial decision support system

Spatial Decision Support System (SDSS) assist in strategic decision-making activities considering spatial and temporal variables, which help in Regional planning. WEPA is a SDSS designed for assessment of wind potential spatially. A wind energy system transforms the kinetic energy of the wind into mechanical or electrical energy that can be harnessed for practical use. Wind energy can diversify the economies of rural communities, adding to the tax base and providing new types of income. Wind turbines can add a new source of property value in rural areas that have a hard time attracting new industry. Wind speed is extremely important parameter for assessing the amount of energy a wind turbine can convert to electricity: The energy content of the wind varies with the cube (the third power) of the average wind speed. Estimation of the wind power potential for a site is the most important requirement for selecting a site for the installation of a wind electric generator and evaluating projects in economic terms. It is based on data of the wind frequency distribution at the site, which are collected from a meteorological mast consisting of wind anemometer and a wind vane and spatial parameters (like area available for setting up wind farm, landscape, etc.). The wind resource is governed by the climatology of the region concerned and has large variability with reference to space (spatial expanse) and time (season) at any fixed location. Hence the need to conduct wind resource surveys and spatial analysis constitute vital components in programs for exploiting wind energy. SDSS for assessing wind potential of a region / location is designed with user friendly GUI’s (Graphic User Interface) using VB as front end with MS Access database (backend). Validation and pilot testing of WEPA SDSS has been done with the data collected for 45 locations in Karnataka based on primary data at selected locations and data collected from the meteorological observatories of the India Meteorological Department (IMD). Wind energy and its characteristics have been analysed for these locations to generate user-friendly reports and spatial maps. Energy Pattern Factor (EPF) and Power Densities are computed for sites with hourly wind data. With the knowledge of EPF and mean wind speed, mean power density is computed for the locations with only monthly data. Wind energy conversion systems would be most effective in these locations during May to August. The analyses show that coastal and dry arid zones in Karnataka have good wind potential, which if exploited would help local industries, coconut and areca plantations, and agriculture. Pre-monsoon availability of wind energy would help in irrigating these orchards, making wind energy a desirable alternative.

Tracking analysis of an LMS decision feedback equalizer for a wireless channel

We consider a time varying wireless fading channel, equalized by an LMS Decision Feedback equalizer (DFE). We study how well this equalizer tracks the optimal MMSEDFE (Wiener) equalizer. We model the channel by an Autoregressive (AR) process. Then the LMS equalizer and the AR process are jointly approximated by the solution of a system of ODEs (ordinary differential equations). Using these ODEs, we show via some examples that the LMS equalizer moves close to the instantaneous Wiener filter after initial transience. We also compare the LMS equalizer with the instantaneous optimal DFE (the commonly used Wiener filter) designed assuming perfect previous decisions and computed using perfect channel estimate (we will call it as IDFE). We show that the LMS equalizer outperforms the IDFE almost all the time after initial transience.

LMS versus Wiener filter for a decision feedback equalizer

In this paper we study an LMS-DFE. We use the ODE framework to show that the LMS-DFE attractors are close to the true DFE Wiener filter (designed considering the decision errors) at high SNR. Therefore, via LMS one can obtain a computationally efficient way to obtain the true DFE Wiener filter under high SNR. We also provide examples to show that the DFE filter so obtained can significantly outperform the usual DFE Wiener filter (designed assuming perfect decisions) at all practical SNRs. In fact, the performance improvement is very significant even at high SNRs (up to 50%), where the popular Wiener filter designed with perfect decisions, is believed to be closer to the optimal one.

Spatial Decision Support System for Assessing Micro, Mini and Small Hydel Potential

This study describes the design and implementation of DSS for assessment of Mini, Micro and Small Schemes. The design links a set of modelling, manipulation, spatial analyses and display tools to a structured database that has the facility to store both observed and simulated data. The main hypothesis is that this tool can be used to form a core of practical methodology that will result in more resilient in less time and can be used by decision-making bodies to assess the impacts of various scenarios (e.g.: changes in land use pattern) and to review, cost and benefits of decisions to be made. It also offers means of entering, accessing and interpreting the information for the purpose of sound decision making. Thus, the overall objective of this DSS is the development of set of tools aimed at transforming data into information and aid decisions at different scales.

Decision support system for regional electricity planning

Electricity appears to be the energy carrier of choice for modern economics since growth in electricity has outpaced growth in the demand for fuels. A decision maker (DM) for accurate and efficient decisions in electricity distribution requires the sector wise and location wise electricity consumption information to predict the requirement of electricity. In this regard, an interactive computer-based Decision Support System (DSS) has been developed to compile, analyse and present the data at disaggregated levels for regional energy planning. This helps in providing the precise information needed to make timely decisions related to transmission and distribution planning leading to increased efficiency and productivity. This paper discusses the design and implementation of a DSS, which facilitates to analyse the consumption of electricity at various hierarchical levels (division, taluk, sub division, feeder) for selected periods. This DSS is validated with the data of transmission and distribution systems of Kolar district in Karnataka State, India.

Decision tree design and applications in speech processing

The design and operation of the minimum cost classifier, where the total cost is the sum of the measurement cost and the classification cost, is computationally complex. Noting the difficulties associated with this approach, decision tree design directly from a set of labelled samples is proposed in this paper. The feature space is first partitioned to transform the problem to one of discrete features. The resulting problem is solved by a dynamic programming algorithm over an explicitly ordered state space of all outcomes of all feature subsets. The solution procedure is very general and is applicable to any minimum cost pattern classification problem in which each feature has a finite number of outcomes. These techniques are applied to (i) voiced, unvoiced, and silence classification of speech, and (ii) spoken vowel recognition. The resulting decision trees are operationally very efficient and yield attractive classification accuracies.