Sense of Coherence : Determinants and consequences

ABSTRACT Sense of coherence (SOC) is a core concept within Antonovsky s salutogenic theory and is argued to be a psychological determinant of health. The present social-epidemiological study explores the associations between a wide range of generalized resistance resources of SOC among Finnish- and Swedish-speaking women and men with a view to gaining deeper insight into its developmental circumstances and determinants. Secondly, a five-year follow-up study was conducted in order to assess the stability of SOC in difficult life events. Finally the role and effect of SOC in the intentions to retire early was investigated in a prospective study. The above studies were based on two data sets: the Finnish 'Survey on Living Conditions' (ELO-94) conducted in 1994 by means of personal face-to-face interviews (N=6506), and a prospective postal survey of the 15-year Health and Social Support (HeSSup) study for which the baseline data was collected in 1998 (N=25 898) and the follow-up in 2003. The present study reveals that the level of SOC in adulthood is strongly dependent on close and successful social relationships during both childhood and adulthood, and that there is a strong association with qualitative work features. Not having a partner as well as being unable to use one s skills at work proved to threaten men s SOC in particular, whereas a lack of social support did the same for women. Otherwise, the association with generalized resistance resources turned out to be quite similar in both genders. Swedish-speaking Finns appear to have a slightly stronger SOC due to the better psycho-emotional circumstances in the childhood home and work circumstances in adulthood, in other words higher levels of generalized resistance resources compared to Finnish speakers. These language group differences did not concern any social-life factors included in the present study. The results of the five-year follow-up study suggest that SOC is not stable, and that the level clearly decreases after a negative life event. Even a strong SOC decreased during the follow-up period and, furthermore, was no more stable than a mediocre or weak SOC. There seems to be a clear and independent association with the intentions to retire early among both men and women following full adjustment. Swedish speakers appear to be less inclined to retire early than Finnish speakers. In the light of the present study, it seems that SOC is determined not only by socio-economic factors but also by close and successful social relationships during both childhood and adulthood. This applied to both genders and language groups. Interventions aimed at promoting the health of the disadvantaged should therefore focus on families with children, and extend later also to other than socio-economic spheres of life. SOC theory could also be applied in efforts to inhibit early retirement: management practices aimed at providing employees with a work environment and tasks that are comprehensible, manageable and meaningful could potentially decrease the intentions to retire early.

Making sense of a transnational merger: Media texts and the (re)construction of power relations

In this study of symbolic power relations in a transnational merger, we suggest that the popular media can provide a significant arena for (re)constructing national identities and power in this kind of dramatic industrial restructuring, and are an under-utilized source of empirical data in research studies. Focusing on the press coverage of a recent Swedish-Finnish merger, we specify and illustrate a particular feature of discursive (re)construction of asymmetric power relations; superior (Swedish) and inferior (Finnish) national identities, which, we argue, are embedded in the history of colonization and domination between the two nations. The findings of the present study lead us to suggest that a lens taken from post-colonial theory is particularly useful in understanding the wider symbolic power implications of international industrial restructuring.

A cost effective pipelined divider for double precision floating point number

he growth of high-performance application in computer graphics, signal processing and scientific computing is a key driver for high performance, fixed latency; pipelined floating point dividers. Solutions available in the literature use large lookup table for double precision floating point operations.In this paper, we propose a cost effective, fixed latency pipelined divider using modified Taylor-series expansion for double precision floating point operations. We reduce chip area by using a smaller lookup table. We show that the latency of the proposed divider is 49.4 times the latency of a full-adder. The proposed divider reduces chip area by about 81% than the pipelined divider in [9] which is based on modified Taylor-series.

COMMON-Sense net:Improved water management for resource-poor farmers via sensor networks

We describe the on-going design and implementation of a sensor network for agricultural management targeted at resource-poor farmers in India. Our focus on semi-arid regions led us to concentrate on water-related issues. Throughout 2004, we carried out a survey on the information needs of the population living in a cluster of villages in our study area. The results highlighted the potential that environment-related information has for the improvement of farming strategies in the face of highly variable conditions, in particular for risk management strategies (choice of crop varieties, sowing and harvest periods, prevention of pests and diseases, efficient use of irrigation water etc.). This leads us to advocate an original use of Information and Communication Technologies (ICT). We believe our demand-driven approach for the design of appropriate ICT tools that are targeted at the resource-poor to be relatively new. In order to go beyond a pure technocratic approach, we adopted an iterative, participatory methodology.

Design of a FIR filter for image restoration using principal component neural networks

The neural network finds its application in many image denoising applications because of its inherent characteristics such as nonlinear mapping and self-adaptiveness. The design of filters largely depends on the a-priori knowledge about the type of noise. Due to this, standard filters are application and image specific. Widely used filtering algorithms reduce noisy artifacts by smoothing. However, this operation normally results in smoothing of the edges as well. On the other hand, sharpening filters enhance the high frequency details making the image non-smooth. An integrated general approach to design a finite impulse response filter based on principal component neural network (PCNN) is proposed in this study for image filtering, optimized in the sense of visual inspection and error metric. This algorithm exploits the inter-pixel correlation by iteratively updating the filter coefficients using PCNN. This algorithm performs optimal smoothing of the noisy image by preserving high and low frequency features. Evaluation results show that the proposed filter is robust under various noise distributions. Further, the number of unknown parameters is very few and most of these parameters are adaptively obtained from the processed image.

An Estimator Algorithm For Learning Automata With Changing Number Of Actions

In many problems of decision making under uncertainty the system has to acquire knowledge of its environment and learn the optimal decision through its experience. Such problems may also involve the system having to arrive at the globally optimal decision, when at each instant only a subset of the entire set of possible alternatives is available. These problems can be successfully modelled and analysed by learning automata. In this paper an estimator learning algorithm, which maintains estimates of the reward characteristics of the random environment, is presented for an automaton with changing number of actions. A learning automaton using the new scheme is shown to be e-optimal. The simulation results demonstrate the fast convergence properties of the new algorithm. The results of this study can be extended to the design of other types of estimator algorithms with good convergence properties.

Design of crosspoint-irredundant PLAs using minimal number of control inputs

The problem of determining a minimal number of control inputs for converting a programmable logic array (PLA) with undetectable faults to crosspoint-irredundant PLA for testing has been formulated as a nonstandard set covering problem. By representing subsets of sets as cubes, this problem has been reformulated as familiar problems. It is noted that this result has significance because a crosspoint-irredundant PLA can be converted to a completely testable PLA in a straightforward fashion, thus achieving very good fault coverage and easy testability.

Evolution of polyandry by reduction in progeny number variance in structured populations

When there is a variation in the quality of males in a population, multiple mating can lead to an increase in the genetic fitness of a female by reducing the variance of the progeny number. The extent of selective advantage obtainable by this process is investigated for a population subdivided into structured demes. It is seen that for a wide range of model parameters (deme size, distribution of male quality, local resource level), multiple mating leads to a considerable increase in the fitness. Frequency-dependent selection or a stable coexistence between polyandry and monandry can also result when the possible costs involved in multiple mating are taken into account.

On Finding the Natural Number of Topics with Latent Dirichlet Allocation: Some Observations

It is important to identify the ``correct'' number of topics in mechanisms like Latent Dirichlet Allocation(LDA) as they determine the quality of features that are presented as features for classifiers like SVM. In this work we propose a measure to identify the correct number of topics and offer empirical evidence in its favor in terms of classification accuracy and the number of topics that are naturally present in the corpus. We show the merit of the measure by applying it on real-world as well as synthetic data sets(both text and images). In proposing this measure, we view LDA as a matrix factorization mechanism, wherein a given corpus C is split into two matrix factors M-1 and M-2 as given by C-d*w = M1(d*t) x Q(t*w).Where d is the number of documents present in the corpus anti w is the size of the vocabulary. The quality of the split depends on ``t'', the right number of topics chosen. The measure is computed in terms of symmetric KL-Divergence of salient distributions that are derived from these matrix factors. We observe that the divergence values are higher for non-optimal number of topics - this is shown by a `dip' at the right value for `t'.

“Aivan sama vaikkei ne olis edes pelannut” – Jalkapallo elämyskulutuksen kohteena

Tutkielmassa tarkastellaan jalkapallon seuraamista elämyskuluttamisen näkökulmasta. Elämyskulutuksella tarkoitetaan tässä yhteydessä tapahtumia ja hetkiä, jolloin ihminen kokee tavallisuudesta poikkeavan ja mieleenpainuvan tunnetilan. Elämyksiä tarjoavat palvelut ovat lisänneet jatkuvasti suosiotaan, kun arjessa rationaalisuus ylikorostuu ja sille halutaan vastapainoa. Aihetta taustoitetaan elämysyhteiskunnan, yhteisöllisyyden ja kuluttajaheimojen käsitteiden avulla. Erityishuomion saavat kulttuuritapahtumat elämystuotteina, penkkiurheilu yhteiskunnallisena ilmiönä sekä erilaiset jalkapalloon liittyvät kulutustavat. Tutkielma on luonteeltaan fenomenologis-etnografinen kuvaileva tutkimus. Tutkimusmenetelminä on käytetty osallistuvaa havainnointia ja haastatteluita. Tutkimusperinteen mukaisesti ilmiön ymmärtäminen, kuvaaminen ja kirjoittaminen ovat tärkeässä osassa. Havainnointiaineisto on kerätty kolmessa eri tapahtumassa seuraamalla katsojien käyttäytymistä ja tunnelman syntymiseen vaikuttavia tekijöitä. Haastateltavat on valittu harkinnanvaraisesti jalkapalloa aktiivisesti seuraavista henkilöistä ja menetelmänä on käytetty avoimia teemahaastatteluita. Urheilun vetovoima ajanvietteenä perustuu vahvojen tunteiden herättämiseen, joten penkkiurheilu on elämyskulutusta puhtaimmillaan. Urheilu elämystuotteena on oivallinen, sillä sen lukuisten kulutustapojen lisäksi tapahtumat muodostavat päättymättömän jatkumon. Myös oman aineistoni perusteella osoittautui, että menneiden tapahtumien avulla ankkuroidutaan yhteisöön ja tulevien tapahtumien avulla pidetään innostusta yllä. Pettymysten hetkelläkään koukusta ei haluta irti, sillä jokainen kokemus lisää tunteita omaa urheilulajia ja yhteisöä kohtaan. Urheilutapahtumissa katsojan elämys syntyy subjektiivisen kokemuksen kautta, mutta yhteisö luo elämyksen toteutumisen välttämättömät edellytykset. Jalkapalloyleisöön kuuluvissa henkilöissä yhdistyvät halu kuulua ryhmään ja olla samaan aikaan sen ulkopuolella. Peliä voidaan tarkkailla itsekseen ja keskittyneesti suuren joukon keskellä tai hurrata muiden mukana. Aineistoni perusteella jalkapallofanin innostus pulppuaa kahdesta lähteestä: yhteisöllisyydestä ja kiinnostuksesta lajiin. Yhteisöllisyyden tunne syntyy kuulumisesta globaaliin jalkapalloyhteisöön, oman suosikkijoukkueen kannattajiin ja samaa lajia seuraavien kaverien muodostamaan lähipiiriin. Urheilullinen puoli innostuksesta syntyy kiinnostuksesta jalkapalloa kohtaan lajina, aktiivisesti seuratuista säännöllisistä tapahtumista ja oman joukkueen kannattamisesta. Jalkapallon seuraajiin teoria jatkuvasti muuttuvista uusyhteisöistä pätee melko huonosti, sillä lajille ja seuralle ollaan hyvin uskollisia. Faneille on tärkeää sitoutua pieneen lähiyhteisöön, jonka kanssa heillä on yhteinen historia ja mahdollisuus jakaa kokemuksia keskustelemalla ja muistelemalla.

Design of speaker identification schemes for large number of speakers (A)

Design of speaker identification schemes for a small number of speakers (around 10) with a high degree of accuracy in controlled environment is a practical proposition today. When the number of speakers is large (say 50–100), many of these schemes cannot be directly extended, as both recognition error and computation time increase monotonically with population size. The feature selection problem is also complex for such schemes. Though there were earlier attempts to rank order features based on statistical distance measures, it has been observed only recently that the best two independent measurements are not the same as the combination in two's for pattern classification. We propose here a systematic approach to the problem using the decision tree or hierarchical classifier with the following objectives: (1) Design of optimal policy at each node of the tree given the tree structure i.e., the tree skeleton and the features to be used at each node. (2) Determination of the optimal feature measurement and decision policy given only the tree skeleton. Applicability of optimization procedures such as dynamic programming in the design of such trees is studied. The experimental results deal with the design of a 50 speaker identification scheme based on this approach.