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  • 1.
    Alam, Moudud
    Dalarna University, School of Technology and Business Studies, Statistics.
    An efficient algorithm for the pseudo likelihood estimation of the generalized linear mixed models (GLMM) with correlated random effects2009Report (Other academic)
    Abstract [en]

    This paper presents a two-step pseudo likelihood estimation technique for generalized linear mixed models with correlated random effects. The proposed estimation technique does not require reparametarisation of the model. Multivariate Taylor's approximation has been used to approximate the intractable integrals in the likelihood function of the GLMM. Based on the analytical expression for the estimator of the covariance matrix of the random effects, a condition has been presented as to when such a covariance matrix can be estimated through the estimates of the random effects. An application of the model with a binary response variable has been presented using a real data set on credit defaults from two Swedish banks. Due to the use of two-step estimation technique, proposed algorithm outperforms the conventional pseudo likelihood algorithms in terms of computational time.

  • 2.
    Alam, Moudud
    Dalarna University, School of Technology and Business Studies, Statistics.
    An efficient estimation of the GLMM with correlated random effects2008In: COMPSTAT'2008: International Conference on Computational Statistics / [ed] Moudud, Alam, Porto-Portugal, 2008Conference paper (Other academic)
    Abstract [en]

    This paper presents a two-step pseudo likelihood estimation technique for the generalized linear mixed models (GLMM) with random effects being correlated (possibly between subjects). Due to the use of the two-step estimation technique the proposed algorithm outperforms the conventional pseudo likelihood algorithms, e.g. Wolfinger and O’Connell (1993), in terms of computational time. Moreover, it does not require any reparametarisation of the model such as Lindstrom and Bates (1989). Multivariate Taylor’s approximation has been used to approximate the intractable integrals in the likelihood function of the GLMM. Based on the analytical expression for the estimator of the covariance matrix of the random effects, a condition has been presented as to when such a covariance matrix can be estimated through the estimates of the random effects. An application of the estimation technique with a binary response variable is presented using a real data set on credit defaults.

  • 3.
    Alam, Moudud
    Dalarna University, School of Technology and Business Studies, Statistics.
    Feasible computation of the generalized linear mixed models with application to credit risk modelling2010Doctoral thesis, monograph (Other academic)
    Abstract [en]

    This thesis deals with developing and testing feasible computational procedures to facilitate the estimation of and carry out the prediction with the generalized linear mixed model (GLMM) with a scope of applying them to large data sets. The work of this thesis is motivated from an issue arising in credit risk modelling. We have access to a huge data set, consisting of about one million observations, on credit history obtained from two major Swedish banks. The principal research interest involved with the data analysis is to model the probability of credit defaults by incorporating the systematic dependencies among the default events. In order to model the dependent credit defaults we adopt the framework of GLMM which is a popular approach to model correlated binary data. However, existing computational procedures for GLMM did not offer us the flexibility to incorporate the desired correlation structure of defaults events. For the feasible estimation of the GLMM we propose two estimation techniques being the fixed effects (FE) approach and the two-step pseudo likelihood approach (2PL). The preciseness of the estimation techniques and their computational advantages are studied by Monte-Carlo simulations and by applying them to the credit risk modelling. Regarding the prediction issue, we show how to apply the likelihood principle to carry out prediction with GLMM. We also provide an R add-in package to facilitate the predictive inference for GLMM.

  • 4.
    Alam, Moudud
    Dalarna University, School of Technology and Business Studies, Statistics.
    Feasible estimation of generalized linear mixed models (GLMM) with weak dependency between groups2010Manuscript (preprint) (Other academic)
    Abstract [en]

    This paper presents a two-step pseudo likelihood estimation technique for generalized linear mixed models with the random effects being correlated between groups. The core idea is to deal with the intractable integrals in the likelihood function by multivariate Taylor's approximation. The accuracy of the estimation technique is assessed in a Monte-Carlo study. An application of it with a binary response variable is presented using a real data set on credit defaults from two Swedish banks. Thanks to the use of two-step estimation technique, the proposed algorithm outperforms conventional pseudo likelihood algorithms in terms of computational time.

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  • 5.
    Alam, Moudud
    Dalarna University, School of Technology and Business Studies, Statistics.
    Industry shocks and empirical evidences on defaults comovement2009Report (Other academic)
    Abstract [en]

    It is commonly agreed that the credit defaults are correlated. However, the mechanism of such dependence is not yet fully understood. This paper contributes to the current understanding about the defaults comovement in the following way. Assuming that the industries provides the basis of defaults comovement it provides empirical evidence as to how such comovements can be modeled using correlated industry shocks. Generalized linear mixed model (GLMM) with correlated random effects is used to model the defaults comovement. Empirical evidences are drawn through analyzing individual borrower level credit history data obtained from two major Swedish banks between the period 1994-2000. The results show that the defaults are correlated both within and between industries but not over time (quarters). A discussion has also been presented as to how a GLMM for defaults correlation can be explained.

  • 6.
    Alam, Moudud
    Dalarna University, School of Technology and Business Studies, Statistics.
    Likelihood prediction for generalized linear mixed models under covariate uncertainty2014In: Communications in Statistics - Theory and Methods, ISSN 0361-0926, E-ISSN 1532-415X, Vol. 43, no 2, p. 219-234Article in journal (Refereed)
    Abstract [en]

    This paper presents the techniques of likelihood prediction for the generalized linear mixed models. Methods of likelihood prediction is explained through a series of examples; from a classical one to more complicated ones. The examples show, in simple cases, that the likelihood prediction (LP) coincides with already known best frequentist practice such as the best linear unbiased predictor. The paper outlines a way to deal with the covariate uncertainty while producing predictive inference. Using a Poisson error-in-variable generalized linear model, it has been shown that in complicated cases LP produces better results than already know methods.

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  • 7.
    Alam, Moudud
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Carling, Kenneth
    Dalarna University, School of Technology and Business Studies, Statistics.
    Computionally feasible estimation of the covariance structure in generalized linear mixed models2008In: Journal of Statistical Computation and Simulation, ISSN 0094-9655, E-ISSN 1563-5163, Vol. 78, no 12, p. 1229-1239Article in journal (Refereed)
    Abstract [en]

    In this paper, we discuss how a regression model, with a non-continuous response variable, which allows for dependency between observations, should be estimated when observations are clustered and measurements on the subjects are repeated. The cluster sizes are assumed to be large. We find that the conventional estimation technique suggested by the literature on generalized linear mixed models (GLMM) is slow and sometimes fails due to non-convergence and lack of memory on standard PCs. We suggest to estimate the random effects as fixed effects by generalized linear model and to derive the covariance matrix from these estimates. A simulation study shows that our proposal is feasible in terms of mean-square error and computation time. We recommend that our proposal be implemented in the software of GLMM techniques so that the estimation procedure can switch between the conventional technique and our proposal, depending on the size of the clusters.

  • 8.
    Alam, Moudud
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Carling, Kenneth
    Dalarna University, School of Technology and Business Studies, Statistics.
    Chen, Rui
    Liang, Yuli
    How to determine the progression of young skiers?2008In: CHANCE: New Directions for Statistics and Computing, ISSN 0933-2480, Vol. 21, no 4, p. 13-19Article in journal (Refereed)
  • 9.
    Alam, Moudud
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Carling, Kenneth
    Dalarna University, School of Technology and Business Studies, Statistics.
    Linde, Olof
    Sweco Eurofutures.
    Nääs, Ola
    Dalarna University, School of Technology and Business Studies, Statistics.
    Sandén, Peter
    Sweco Eurofutures.
    Wing, Stefan
    Sweco Eurofutures.
    Utvärdering av det arbetsmarknadspolitiska projektet "Volvo Cars och dess underleverantörer"2012Report (Other academic)
    Abstract [sv]

    Denna rapport är en utvärdering av det arbetsmarknadspolitiska projektet "Volvo Cars och dess underleverantörer", som har genomförts av Arbetsförmedlingen i samarbete med Skolverket och Svenska ESF-rådet. Den 5 juni 2009 ansökte Sveriges regering om medel hos den Europeiska globaliseringsfonen (EGF)2 för att kunna erbjuda åtgärder för personer som blivit uppsagda från Volvo Cars AB och dess underleverantörer. Syftet med projektet var att kunna erbjuda de som blivit uppsagda kompetensutveckling, nya yrkeskunskaper och möjlighet att etablera egna företag.

    På operativ nivå drevs projektet i samverkan mellan Arbetsförmedlingen och den kom-munala yrkesvuxenutbildningen ("Yrkesvux"). Yrkesvux i Göteborgs kommun fick i upp-drag av Skolverket att samordna den del av verksamheten som berörde kommunal yr-kesvuxenutbildning. Projektet startade 1 januari 2010 och avslutades 31 maj 2011. Enligt kommissionens beslut fick medel även användas retroaktivt för insatser som hade givits till de uppsagda i form av olika arbetsmarknadsutbildningar, det s.k. snabbspåret, under 2009 innan projektet hade startat.

    Av nästan 5 000 individer i målgruppen som registrerade sig vid Arbetsförmedlingen del-tog knappt en fjärdedel i projektets insatser (exkl. vägledning). Av dessa gick 55 procent i aktiviteter enbart genom Arbetsförmedlingen, 37 procent enbart genom Yrkesvux och åtta procent genom både Arbetsförmedlingen och Yrkesvux. De vanligaste förekommande utbildningsinriktningarna var industri och bygg, fordonsindustri, transport och magasine-ring, omvårdnad och handel.

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  • 10.
    Alam, Moudud
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Carling, Kenneth
    Dalarna University, School of Technology and Business Studies, Statistics.
    Nääs, Ola
    Dalarna University, School of Technology and Business Studies, Statistics.
    Har kommunala sommarjobb under gymnasieåren en positiv effekt på arbetskarriären senare i livet?2013Report (Other academic)
    Abstract [sv]

    Att erbjuda sommarjobb till ungdomar ses i många länder som ett sätt att förbättra ungdomars möjligheter att komma in och etablera sig på arbetsmarknaden. I Sverige erbjuder de flesta kommuner, delvis finansierat med statliga medel, sommarjobb till ungdomar. Den forskning som finns kring effekten av sommarjobb för ungdomar pekar dock i olika riktningar och lider ofta av metodproblem. Vi undersöker här med bättre metodologiska förutsättningar om kommunala sommarjobb för gymnasieungdomar i Falu kommun har någon positiv effekt på den postgymnasiala inkomstutvecklingen. Vi följer 2 650 ungdomar som, under första året i gymnasiet, ansökte om kommunalt sommarjobb. Vi följer dem tills de når en ålder av som mest 29 år. De kommunala sommarjobben fördelades genom ett lotteriförfarande där alla som ansökte hade lika stor chans att bli tilldelad ett sommarjobb. Vi finner ingen programeffekt för män. För kvinnor upptäcker vi en positiv effekt och då speciellt för kvinnor med låga betyg från grundskolan.

  • 11.
    Alam, Moudud
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Carling, Kenneth
    Dalarna University, School of Technology and Business Studies, Statistics.
    Nääs, Ola
    Dalarna University, School of Technology and Business Studies, Statistics.
    High-School Students´ Summer Jobs and their Ensuing Labor Market Achievement: the Long Term Effect2013Report (Other academic)
    Abstract [en]

    In part because of high and persistent youth unemployment, adolescent students’ transition from school to work is an important policy and research topic. Many countries have implemented public programs offering summer jobs or work while in high-school as measures to smooth the transition. While the immediate effect of the programs on school attendance, school grades, and disposable income is well documented, their effect on the transition to the labor market remains an open question. Observational studies have shown strong positive effects of summer jobs, but also that the estimated effect is highly vulnerable to selection bias. In this paper, some 3700 high-school students applying for summer jobs in the period 1995-2003,via a program, are followed to 30 years of age. A quarter of the applicants were randomly offered a summer job each year. Among the remaining students, 50% had a (non-program related) summer job while in high-school. We find the income, post high-school, for the offered and non-offered groups to be similar and conclude that the effect of summer jobs on the transition to the labor market is inconsequential.

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  • 12.
    Alam, Moudud
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Carling, Kenneth
    Dalarna University, School of Technology and Business Studies, Statistics.
    Nääs, Ola
    Dalarna University, School of Technology and Business Studies, Statistics.
    Sommarjobb, arbetslivserfarenhet och framtida arbetsinkomst2015In: Arbetsmarknad & Arbetsliv, ISSN 1400-9692, E-ISSN 2002-343X, Vol. 21, no 4, p. 26-40Article in journal (Refereed)
    Abstract [sv]

    De flesta kommuner erbjuder sommarjobb till gymnasieungdomar. Vi har undersökt om denna arbetslivserfarenhet påverkar flickors framtida arbetsinkomster. Vi följde 1 447 flickor i fem till tolv år efter avslutat gymnasium. Flickorna hade under sitt första gymnasieår ansökt och slumpmässigt tilldelats sommarjobb av Falu kommun. Effekten av sommarjobbserfarenheten var positiv och betydande för dem.

  • 13.
    Alam, Moudud
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Carling, Kenneth
    Dalarna University, School of Technology and Business Studies, Statistics.
    Nääs, Ola
    Dalarna University, School of Technology and Business Studies, Statistics.
    The effect of summer jobs on post-schooling incomes2013Report (Other academic)
    Abstract [en]

    In part because of high youth unemployment, students’ transition from school to work is an important policy and research topic. Public programs offering summer jobs or work while in high school as measures to smooth the transition is commonplace. The immediate effect of the programs on school attendance, school grades, and disposable income is well documented. However, their effect on the transition to the labor market remains unsettled, partly because of a potential selection bias in previous observational studies. In this paper, 2650 first graders of high school in Falun Council, Sweden, randomly allotted summer jobs via a program in the years of 1997-2003, are followed ten years after graduation. The program led to a substantially larger accumulation of work experience while in high school for offered (particularly weak academically performing) females, but not for offered males. Hence, the immediate program effect was heterogeneous. Females were used to estimate the causal effect of work experience while in high school on post-schooling incomes. The (statistically) significant estimate implies an elasticity of 0.4. Work experience while in high school seems to be of future benefit, but the elasticity is potentially inflated due to heterogeneous effects that we were unable to account for.

  • 14.
    Alam, Moudud
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Carling, Kenneth
    Dalarna University, School of Technology and Business Studies, Statistics.
    Nääs, Ola
    Dalarna University, School of Technology and Business Studies, Statistics.
    The program and treatment effect of summer jobs on girls’ post-schooling incomes2015In: Evaluation review, ISSN 0193-841X, E-ISSN 1552-3926, Vol. 39, no 3, p. 339-359Article in journal (Refereed)
    Abstract [en]

    Background: Public programs offering summer jobs to smooth the transition from school to work is commonplace. However, the empirical support for summer jobs is limited. This article exploits the availability of registered individual information and random allocation to summer jobs to provide empirical evidence on this issue. 

    Objectives: To identify the effect of summer job programs on the post-schooling incomes of the intended participants. Also to identify the effect of sophomore girls' high school work experience on their post-schooling incomes. 

    Research design: In this article, 1,447 sophomore girls from 1997 to 2003 are followed 5-12 years after graduation. They all applied to Falun municipality's (Sweden) summer job program, and about 25% of them were randomly allotted a job. The random allocation to a summer job is used to identify the causal effect of sophomore girls' high school income on their post-schooling incomes. 

    Subjects: All the 1,447 sophomore girls who applied to Falun municipality's summer job program during 1997-2003. 

    Measures: Annual post-schooling income is used as an outcome measure. The work experience of girls in high school is also measured in terms of total income while in high school. 

    Results: The program led to a substantially larger accumulation of income during high school as well as 19% higher post-schooling incomes. The high school income led to a post-schooling income elasticity of 0.37 which is, however, potentially heterogeneous with regard to academic ability. 

    Conclusions: Both the program effect and the causal effect of high school income on post-schooling incomes were substantial and statistically significant.

  • 15.
    Alam, Moudud
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Carling, Kenneth
    Dalarna University, School of Technology and Business Studies, Statistics.
    Nääs, Ola
    Dalarna University, School of Technology and Business Studies, Statistics.
    The program and treatment effect of summer jobs on girls’ post-schooling incomes2014Report (Other academic)
    Abstract [en]

    Public programs (of disputed effect) offering summer jobs or work while in high school to smooth the transition from school to work is commonplace. In this paper, 1447 girls in their first grade of high school between 1997-2003 and randomly allotted summer jobs via a program in Falun (Sweden) are followed 5-12 years after graduation. The program led to a substantially larger accumulation of income while in high school. The causal effect of the high school income on post-schooling incomes was substantial and statistically significant. The implied elasticity of 0.4 is however potentially inflated dueto heterogeneous effects.

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  • 16.
    Alam, Moudud
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Hao, Chengcheng
    Carling, Kenneth
    Dalarna University, School of Technology and Business Studies, Statistics.
    Review of the literature on credit risk modeling: development of the past 10 years2010In: Banks and Bank Systems, ISSN 1816-7403, Vol. 5, no 3, p. 43-60Article in journal (Refereed)
    Abstract [en]

    This paper traces the developments of credit risk modeling in the past 10 years. Our work can be divided into two parts: selecting articles and summarizing results. On the one hand, by constructing an ordered logit model on historical Journal of Economic Literature (JEL) codes of articles about credit risk modeling, we sort out articles which are the most related to our topic. The result indicates that the JEL codes have become the standard to classify researches in credit risk modeling. On the other hand, comparing with the classical review Altman and Saunders(1998), we observe some important changes of research methods of credit risk. The main finding is that current focuses on credit risk modeling have moved from static individual-level models to dynamic portfolio models.

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  • 17.
    Alam, Moudud
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Maengseok, Noh
    Department of Statistics, Pukyong National University, South Korea.
    Lee, Youngjo
    Department of Statistics, Seoul National University, South Korea.
    Likelihood estimate of treatment effects under selection bias2013In: Statistics and its Interface, ISSN 1938-7989, E-ISSN 1938-7997, Vol. 6, no 3, p. 349-359Article in journal (Refereed)
    Abstract [en]

    We consider methods for estimating the causal effects of treatment in the situation where the individuals in the treatment and the control group are self selected, i.e., the selection mechanism is not randomized. In this case, a simple comparison of treated and control outcomes will not generally yield valid estimates of casual effect. The propensity score method is frequently used for the evaluation of treatment effect. However, this method is based on some strong assumptions, which are not directly testable. In this paper, we present an alternative modelling approach to draw causal inferences by using a shared random-effect model and the computational algorithm to draw likelihood based inference with such a model. With small numerical studies and a real data analysis, we show that our approach gives not only more efficient estimates but also is less sensitive to model misspecifications, which we consider, than existing methods.

  • 18.
    Alam, Moudud
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Noh, Maengseok
    Department of Statistics, Pukyong National Univeristy.
    Lee, Youngjo
    Department of Statistics, Seoul National Univeristy.
    Likelihood estimate of treatment effects under selection bias2012Report (Other academic)
    Abstract [en]

    We consider methods for estimating causal effects of treatment in the situation where the individuals in the treatment and the control group are self selected, i.e., the selection mechanism is not randomized. In this case, simple comparison of treated and control outcomes will not generally yield valid estimates of casual effects. The propensity score method is frequently used for the evaluation of treatment effect. However, this method is based onsome strong assumptions, which are not directly testable. In this paper, we present an alternative modeling approachto draw causal inference by using share random-effect model and the computational algorithm to draw likelihood based inference with such a model. With small numerical studies and a real data analysis, we show that our approach gives not only more efficient estimates but it is also less sensitive to model misspecifications, which we consider, than the existing methods.

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  • 19.
    Alam, Moudud
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Rönnegård, Lars
    Dalarna University, School of Technology and Business Studies, Statistics.
    Shen, Xia
    Karolinska Institutet.
    Fitting conditional and simultaneous autoregressive spatial models in hglm2015In: The R Journal, E-ISSN 2073-4859, Vol. 7, no 2, p. 5-18Article in journal (Refereed)
    Abstract [en]

    We present a new version (> 2.0) of the hglm package for fitting hierarchical generalized linear models (HGLMs) with spatially correlated random effects. CAR() and SAR() families for conditional and simultaneous autoregressive random effects were implemented. Eigen decomposition of the matrix describing the spatial structure (e.g., the neighborhood matrix) was used to transform the CAR/SAR random effects into an independent, but eteroscedastic, Gaussian random effect. A linear predictor is fitted for the random effect variance to estimate the parameters in the CAR and SAR models. This gives a computationally efficient algorithm for moderately sized problems.

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  • 20.
    Alam, Moudud
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Rönnegård, Lars
    Dalarna University, School of Technology and Business Studies, Statistics.
    Shen, Xia
    Swedish University of Agricultural Sciences, Uppsala.
    Fitting spatial models in the R package: hglm2014Report (Other academic)
    Abstract [en]

    We present a new version of the hglm package for fittinghierarchical generalized linear models (HGLM) with spatially correlated random effects. A CAR family for conditional autoregressive random effects was implemented. Eigen decomposition of the matrix describing the spatial structure (e.g. the neighborhood matrix) was used to transform the CAR random effectsinto an independent, but heteroscedastic, gaussian random effect. A linear predictor is fitted for the random effect variance to estimate the parameters in the CAR model.This gives a computationally efficient algorithm for moderately sized problems (e.g. n<5000).

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  • 21.
    Alam, Moudud
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Wang, Yu
    When are non-experimental estimates close to experimental estimates?: Evidence from a study of summer job effects in Sweden2007Report (Other academic)
  • 22. Arzpeyma, N.
    et al.
    Alam, Moudud
    Dalarna University, School of Information and Engineering, Statistics.
    Gyllenram, R.
    Jönsson, P. G.
    Model development to study uncertainties in electric arc furnace plants to improve their economic and environmental performance2021In: Metals, ISSN 2075-4701, Vol. 11, no 6, article id 892Article in journal (Refereed)
    Abstract [en]

    A statistical model is developed in order to simulate the melt composition in electric arc furnaces (EAFs) with respect to uncertainties in 1) scrap composition, 2) scrap weighing and 3) element distribution factors. The tramp element Cu and alloying element Cr are taken into account. The model enables simulations of a charge program as well as backwards estimations of the element concentrations and their variance in scrap. In the backwards calculation, the maximum likelihood method is solved by considering three cases corresponding to the involved uncertainties. It is shown that the model can estimate standard deviations for elements so that the real values lie within the estimated 95% confidence interval. Moreover, the results of the model application in each target product show that the estimated scrap composition results in a melt composition, which is in good agreement with the measured one. The model can be applied to increase our understanding of scrap chemical composition and lower the charged material cost and carbon footprint of the products. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.

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  • 23.
    Borg, Johan
    et al.
    Dalarna University, School of Health and Welfare, Medical Science.
    Alam, Moudud
    Dalarna University, School of Information and Engineering, Statistics.
    Boström, Anne-Marie
    Karolinska Institutet, Huddinge; Karolinska University Hospital, Stockholm; Stockholms Sjukhem, Stockholm.
    Marmstål Hammar, Lena
    Dalarna University, School of Health and Welfare, Caring Science/Nursing. Karolinska Institutet, Huddinge; Mälardalen University, Västerås.
    Experiences of Assistive Products and Home Care among Older Clients with and without Dementia in Sweden2022In: International Journal of Environmental Research and Public Health, ISSN 1661-7827, E-ISSN 1660-4601, Vol. 19, no 19, article id 12350Article in journal (Refereed)
    Abstract [en]

    The purpose was to compare selection, use and outcomes of assistive products among older home care clients with and without dementia in Sweden, and to explore the relations between the use of assistive products and perceptions of home care, loneliness and safety. Self-reported data from 89,811 home care clients aged 65 years or more, of whom 8.9% had dementia, were analysed using regression models. Excluding spectacles, 88.2% of them used assistive products. Respondents without dementia were more likely to use at least one assistive product but less likely to use assistive products for remembering. Respondents with dementia participated less in the selection of assistive products, used less assistive products, and benefited less from them. Users of assistive products were more likely to be anxious and bothered by loneliness, to feel unsafe at home with home care, to experience that their opinions and wishes regarding assistance were disregarded by home care personnel, and to be treated worse by home care personnel. The findings raise concerns about whether the needs for assistive products among home care clients with dementia are adequately provided for. They also indicate a need to strengthen a person-centred approach to providing home care to users of assistive products.

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  • 24.
    Johansson-Pajala, Rose-Marie
    et al.
    Mälardalen University, Eskilstuna/Västerås, Sweden.
    Alam, Moudud
    Dalarna University, School of Information and Engineering, Statistics.
    Gusdal, Annelie
    Mälardalen University, Eskilstuna/Västerås, Sweden.
    Heideken Wågert, Petra von
    Mälardalen University, Eskilstuna/Västerås, Sweden.
    Löwenmark, Annica
    Mälardalen University, Eskilstuna/Västerås, Sweden.
    Boström, Anne-Marie
    Mälardalen University, Eskilstuna/Västerås, Sweden; Karolinska Institutet, Stockholm, Sweden; Stockholms Sjukhem, Stockholm, Sweden.
    Marmstål Hammar, Lena
    Dalarna University, School of Health and Welfare, Caring Science/Nursing. Mälardalen University, Eskilstuna/Västerås, Sweden; Karolinska Institutet, Stockholm, Sweden.
    Anxiety and loneliness among older people living in residential care facilities or receiving home care services in Sweden during the COVID-19 pandemic: a national cross-sectional study2022In: BMC Geriatrics, ISSN 1471-2318, E-ISSN 1471-2318, Vol. 22, no 1, article id 927Article in journal (Refereed)
    Abstract [en]

    BACKGROUND: Older people were subjected to significant restrictions on physical contacts with others during the COVID-19 pandemic. Social distancing impacts older people's experiences of anxiety and loneliness. Despite a large body of research on the pandemic, there is little research on its effects on older people in residential care facilities (RCF) and in home care services (HCS), who are the frailest of the older population. We aimed to investigate the effect of the first wave of the COVID-19 pandemic in March-May 2020 on experiences of anxiety and loneliness among older people living in RCF or receiving HCS and the impact of the progression of the pandemic on these experiences.

    METHODS: A retrospective cross-sectional design using data from the national user satisfaction survey (March - May 2020) by the Swedish National Board of Health and Welfare. Survey responses were retrieved from 27,872 older people in RCF (mean age 87 years) and 82,834 older people receiving HCS (mean age 84 years). Proportional-odds (cumulative logit) model was used to estimate the degree of association between dependent and independent variables.

    RESULTS: Loneliness and anxiety were more prevalent among the older persons living in RCF (loneliness: 69%, anxiety: 63%) than those receiving HCS (53% and 47%, respectively). Proportional odds models revealed that among the RCF and HCS respondents, the cumulative odds ratio of experiencing higher degree of anxiety increased by 1.06% and 1.04%, respectively, and loneliness by 1.13% and 1.16%, respectively, for 1% increase in the COVID-19 infection rate. Poor self-rated health was the most influential factor for anxiety in both RCF and HCS. Living alone (with HCS) was the most influential factor affecting loneliness. Experiences of disrespect from staff were more strongly associated with anxiety and loneliness in RCF than in HCS.

    CONCLUSION: Older people in RCF or receiving HCS experienced increasing levels of anxiety and loneliness as the first wave of the pandemic progressed. Older people' mental and social wellbeing should be recognized to a greater extent, such as by providing opportunities for social activities. Better preparedness for future similar events is needed, where restrictions on social interaction are balanced against the public health directives.

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  • 25. Johansson-Pajala, Rose-Marie
    et al.
    Alam, Moudud
    Dalarna University, School of Information and Engineering, Statistics.
    K Gusdal, Annelie
    Marmstål Hammar, Lena
    Dalarna University, School of Health and Welfare, Caring Science/Nursing. Mälardalen University.
    Boström, Anne-Marie
    Trust and easy access to home care staff are associated with older adults' sense of security: a Swedish longitudinal study2024In: Scandinavian Journal of Public Health, ISSN 1403-4948, E-ISSN 1651-1905, p. 36830-, article id 14034948241236830Article in journal (Refereed)
    Abstract [en]

    AIM: Older adults are increasingly encouraged to continue living in their own homes with support from home care services. However, few studies have focused on older adults' safety in home care. This study explored associations between the sense of security and factors related to demographic characteristics and home care services.

    METHODS: The mixed longitudinal design was based on a retrospective national survey. The study population consisted of individuals in Sweden (aged 65+ years) granted home care services at any time between 2016 and 2020 (n=82,834-94,714). Multiple ordinal logistic regression models were fitted using the generalised estimation equation method to assess the strength of relationship between the dependent (sense of security) and independent (demographics, health and care-related factors) variables.

    RESULTS: The sense of security tended to increase between 2016 and 2020, and was significantly associated with being a woman, living outside big cities, being granted more home care services hours or being diagnosed/treated for depression (cumulative odds ratio 2-9% higher). Anxiety, poor health and living alone were most strongly associated with insecurity (cumulative odds ratio 17-64% lower). Aside from overall satisfaction with home care services, accessibility and confidence in staff influenced the sense of security most.

    CONCLUSIONS: We stress the need to promote older adults' sense of security for safe ageing in place, as mandated by Swedish law. Home care services profoundly influence older adults' sense of security. Therefore, it is vital to prioritise continuity in care, establish trust and build relationships with older adults. Given the increasing shortage of staff, integrating complementary measures, such as welfare technologies, is crucial to promoting this sense of security.

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  • 26.
    Karim, Hawzheen
    et al.
    Dalarna University, School of Technology and Business Studies, Road Technology.
    Alam, Moudud
    Dalarna University, School of Technology and Business Studies, Statistics.
    Magnusson, Rolf
    Dalarna University, School of Technology and Business Studies, Road Technology.
    Road barrier repair costs and influencing factors2011In: Journal of transportation engineering, ISSN 0733-947X, E-ISSN 1943-5436, Vol. 137, no 5, p. 349-359Article in journal (Refereed)
    Abstract [en]

    This paper presents a study that examines repair costs for different road barrier types and factors that influence these costs. The analyses focused on w-beam and cable barriers used as median barriers. To some extent, pipe barriers, Kohlswa-beam barriers, and concrete barriers were also studied. The influencing factors included in this study were road type, speed limit, barrier type, and seasonal effects. A case study was conducted in four regions of the Swedish Road Administration. Data were collected from 1,625 barrier repairs carried out during 2005 and 2006. The results show that the number of barrier repairs and the average repair cost per vehicle kilometer are higher along collision-free roads than along motorways and 4-lane roads. The results also show that the number of barrier repairs and the average repair cost per vehicle kilometer are higher for cable barrier than for other barrier types. No conclusion can be drawn regarding influence of speed limits on barrier repairs and associated costs as the result from the regions are divergent and not statistically significant. DOI: 10.1061/(ASCE)TE.1943-5436.0000227. (C) 2011 American Society of Civil Engineers.

  • 27.
    Kroese, Adrien
    et al.
    Swedish University of Agricultural sciences, Uppsala.
    Alam, Moudud
    Dalarna University, School of Information and Engineering, Statistics.
    Hernlund, Elin
    Swedish University of Agricultural sciences, Uppsala.
    Berthet, David
    Sony Nordic, Lund.
    Tamminen, Lena-Mari
    Swedish University of Agricultural sciences, Uppsala.
    Fall, Nils
    Swedish University of Agricultural sciences, Uppsala.
    Högberg, Niclas
    Swedish University of Agricultural sciences, Uppsala.
    3D pose estimation to detect posture transition in free-stall housed dairy cows2024In: Journal of Dairy Science, ISSN 0022-0302, E-ISSN 1525-3198Article in journal (Refereed)
    Abstract [en]

    Free stall comfort is reflected in various indicators, including the ability for dairy cattle to display unhindered posture transition movements in the cubicles. To ensure farm animal welfare, it is instrumental for the farm management to be able to continuously monitor occurrences of abnormal motions. Advances in computer vision have enabled accurate kinematic measurements in several fields such as human, equine and bovine biomechanics. An important step upstream to measuring displacement during posture transitions is to determine that the behavior is accurately detected. In this study, we propose a framework for detecting lying to standing posture transitions from 3D pose estimation data. A multi-view computer vision system recorded posture transitions between Dec. 2021 and Apr. 2022 in a Swedish stall housing 183 individual cows. The output data consisted of the 3D coordinates of specific anatomical landmarks. Sensitivity of posture transition detection was 88.2% while precision reached 99.5%. Analyzing those transition movements, breakpoints detected the timestamp of onset of the rising motion, which was compared with that annotated by observers. Agreement between observers, measured by intra-class correlation, was 0.85 between 3 human observers and 0.81 when adding the automated detection. The intra-observer mean absolute difference in annotated timestamps ranged from 0.4s to 0.7s. The mean absolute difference between each observer and the automated detection ranged from 1.0s to 1.3s. There was a significant difference in annotated timestamp between all observer pairs but not between the observers and the automated detection, leading to the conclusion that the automated detection does not introduce a distinct bias. We conclude that the model is able to accurately detect the phenomenon of interest and that it is equatable to an observer.

  • 28. Lee, Youngjo
    et al.
    Alam, Moudud
    Dalarna University, School of Technology and Business Studies, Statistics.
    Noh, M
    Rönnegård, Lars
    Dalarna University, School of Technology and Business Studies, Statistics.
    Skarin, Anna
    Analyzing spatially correlated counts with excessive zeros: a case of modeling the changes of reindeer distribution2013Report (Other academic)
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  • 29.
    Lee, Youngjo
    et al.
    Department of Statistics, Seoul National University, Seoul, Republic of Korea.
    Alam, Moudud
    Dalarna University, School of Technology and Business Studies, Statistics.
    Sandström, Per
    Department of Forest Resource Management, Swedish University of Agricultural Sciences, Umeå.
    Skarin, Anna
    Department of Animal Nutrition and Management, Swedish University of Agricultural Science, Uppsala.
    Estimating zones of influence using threshold regression2020Report (Other academic)
    Abstract [en]

    In environmental impact assessments, it is important to be able to estimate influence of anthropogenic activities on animal populations. To quantify the influence, it is common to estimate how far, in distance, from a given disturbance source there is an influence on the animals’ habitat selection through estimating a zone of influence (ZOI). Usually, ZOI is estimated for one disturbance source at a time. In this work, we demonstrate how threshold regression modelling can be used for estimating ZOI from several possible sources of disturbances, simultaneously. Based on the theoretical properties of different estimation methods for the estimation of threshold regression we select a set of estimation methods and compare their merits through a simulation study and a real data example. The simulation results revealed that Adaptive Lasso, and Hierarchical likelihood (HL) methods, are two reasonable methods for dealing with the problem. HL performed better than Adaptive Lasso in that it had much higher success rate in identifying correct threshold with small sample size whereas Adaptive Lasso requires large sample to assure good performance. While Adaptive lasso needed to be aided with suitable weights, which are not easy to find, HL method did not require any prior weights. These two methods were applied to estimate the ZOI around 40 wind turbines and surrounding public roads on reindeer habitat selection in winter, by using GPS positioning data from 42 reindeer in north of Sweden in December to March (2012-2015). The results showed that both the disturbance sources have a negative effect on reindeer habitat selection in winter. The HL approach showed that the negative ZOI from the nearest wind turbine was 1.8 km (approx.), however the trend of higher selection of areas further away from the wind turbines was evident up to 4 km (approx.) from the active wind turbines.

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  • 30.
    Marmstål Hammar, Lena
    et al.
    Dalarna University, School of Health and Welfare, Caring Science/Nursing. Mälardalen University, Västerås; Karolinska Institutet, Stockholm.
    Alam, Moudud
    Dalarna University, School of Information and Engineering, Statistics.
    Eklund, Caroline
    Mälardalen University, Västerås.
    Boström, Anne-Marie
    Karolinska Institutet, Stockholm; Karolinska University Hospital, Huddinge; Stockholms Sjukhem, Stockholm.
    Lövenmark, Annica
    Mälardalen University, Västerås.
    Clarity and adaptability of instructions preventing the spread of the COVID-19 virus and its association with individual and organisational factors regarding the psychosocial work environment: a cross-sectional study2023In: BMC Health Services Research, E-ISSN 1472-6963, Vol. 23, no 1, article id 1312Article in journal (Refereed)
    Abstract [en]

    BACKGROUND: In Sweden, older people in residential care had the highest mortality rates, followed by those who received home care, during the coronavirus disease 2019 (COVID-19) pandemic. Staff working in the care of older people assumed responsibility for preventing the spread of the virus despite lacking the prerequisites and training. This study aimed to investigate the psychosocial work environment during the COVID-19 pandemic among staff in the care of older people and examine the factors associated with staff's perceptions of the clarity of instructions and the ability to follow them.

    METHODS: A cross-sectional study design was employed using a web survey. The staff's perceptions of their psychosocial environment were analysed using descriptive statistics. The association between organisational and individual factors, as well as the degree of clarity of the instructions and the staff's ability to follow them, were assessed using multivariate (ordinal) regression analysis.

    RESULTS: The main findings show that perceptions of the clarity and adaptability of the instructions were primarily correlated with organisational factors, as higher responses (positive) for the subscales focusing on role clarity, support and encouragement in leadership at work were associated with the belief that the instructions were clear. Similarly, those indicating high job demands and high individual learning demands were less likely to report that the instructions were clear. Regarding adaptability, high scores for demands on learning and psychological demands were correlated with lower adaptability, while high scores for role clarity, encouraging leadership and social support, were associated with higher adaptability.

    CONCLUSIONS: High job demands and individual learning demands were demonstrated to decrease the staff's understanding and adoption of instructions. These findings are significant on an organisational level since the work environment must be prepared for potential future pandemics to promote quality improvement and generally increase patient safety and staff health.

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  • 31.
    Marmstål Hammar, Lena
    et al.
    Dalarna University, School of Health and Welfare, Caring Science/Nursing. Mälardalen University, Karolinska Institute.
    Alam, Moudud
    Dalarna University, School of Information and Engineering, Statistics.
    Olsen, Marie
    Dalarna University, School of Health and Welfare, Caring Science/Nursing. Karolinska Institutet.
    Swall, Anna
    Dalarna University, School of Health and Welfare, Caring Science/Nursing.
    Boström, A. -M
    Being Treated With Respect and Dignity?: Perceptions of Home Care Service Among Persons With Dementia2021In: Journal of the American Medical Directors Association, ISSN 1525-8610, E-ISSN 1538-9375, no 3, p. 656-662Article in journal (Refereed)
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  • 32. Niebuhr, B. B.
    et al.
    Van Moorter, B.
    Stien, A.
    Tveraa, T.
    Strand, O.
    Langeland, K.
    Sandström, P.
    Alam, Moudud
    Dalarna University, School of Information and Engineering, Statistics.
    Skarin, A.
    Panzacchi, M.
    Estimating the cumulative impact and zone of influence of anthropogenic features on biodiversity2023In: Methods in Ecology and Evolution, E-ISSN 2041-210X, Vol. 14, p. 2362-2375Article in journal (Refereed)
    Abstract [en]

    The concept of cumulative impacts is widespread in policy documents, regulations and ecological studies, but quantification methods are still evolving. Infrastructure development usually takes place in landscapes with preexisting anthropogenic features. Typically, their impact is determined by computing the distance to the nearest feature only, thus ignoring the potential cumulative impacts of multiple features. We propose the cumulative ZOI approach to assess whether and to what extent anthropogenic features lead to cumulative impacts. The approach estimates both effect size and zone of influence (ZOI) of anthropogenic features and allows for estimation of cumulative effects of multiple features distributed in the landscape. First, we use simulations and an empirical study to understand under which circumstances cumulative impacts arise. Second, we demonstrate the approach by estimating the cumulative impacts of tourist infrastructure in Norway on the habitat of wild reindeer (Rangifer t. tarandus), a near-threatened species highly sensitive to anthropogenic disturbance. In the simulations, we showed that analyses based on the nearest feature and our cumulative approach are indistinguishable in two extreme cases: when features are few and scattered and their ZOI is small, and when features are clustered and their ZOI is large. The empirical analyses revealed cumulative impacts of private cabins and tourist resorts on reindeer, extending up to 10 and 20 km, with different decaying functions. Although the impact of an isolated private cabin was negligible, the cumulative impact of ‘cabin villages’ could be much larger than that of a single large tourist resort. Focusing on the nearest feature only underestimates the impact of ‘cabin villages’ on reindeer. The suggested approach allows us to quantify the magnitude and spatial extent of cumulative impacts of point, linear, and polygon features in a computationally efficient and flexible way and is implemented in the oneimpact R package. The formal framework offers the possibility to avoid widespread underestimations of anthropogenic impacts in ecological and impact assessment studies and can be applied to a wide range of spatial response variables, including habitat selection, population abundance, species richness and diversity, community dynamics and other ecological processes. © 2023 The Authors. Methods in Ecology and Evolution published by John Wiley & Sons Ltd on behalf of British Ecological Society.

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  • 33. Nowak, Christoph
    et al.
    Carlsson, Axel C.
    Ostgren, Carl Johan
    Nystrom, Fredrik H.
    Alam, Moudud
    Dalarna University, School of Technology and Business Studies, Statistics.
    Rudholm Feldreich, Tobias
    Dalarna University, School of Education, Health and Social Studies, Medical Science.
    Sundstrom, Johan
    Carrero, Juan-Jesus
    Leppert, Jerzy
    Ärnlöv, Johan
    Dalarna University, School of Education, Health and Social Studies, Medical Science. Karolinska Institutet.
    Multiplex proteomics for prediction of major cardiovascular events in type 2 diabetes2018In: Diabetologia, ISSN 0012-186X, E-ISSN 1432-0428, Vol. 61, no 8, p. 1748-1757Article in journal (Refereed)
    Abstract [en]

    Aims/hypothesis Multiplex proteomics could improve understanding and risk prediction of major adverse cardiovascular events (MACE) in type 2 diabetes. This study assessed 80 cardiovascular and inflammatory proteins for biomarker discovery and prediction of MACE in type 2 diabetes. Methods We combined data from six prospective epidemiological studies of 30-77-year-old individuals with type 2 diabetes in whom 80 circulating proteins were measured by proximity extension assay. Multivariable-adjusted Cox regression was used in a discovery/replication design to identify biomarkers for incident MACE. We used gradient-boosted machine learning and lasso regularised Cox regression in a random 75% training subsample to assess whether adding proteins to risk factors included in the Swedish National Diabetes Register risk model would improve the prediction of MACE in the separate 25% test subsample. Results Of 1211 adults with type 2 diabetes (32% women), 211 experienced a MACE over a mean (+/- SD) of 6.4 +/- 2.3 years. We replicated associations (< 5% false discovery rate) between risk of MACE and eight proteins: matrix metalloproteinase (MMP)-12, IL-27 subunit alpha (IL-27a), kidney injury molecule (KIM)-1, fibroblast growth factor (FGF)-23, protein S100-A12, TNF receptor (TNFR)-1, TNFR-2 and TNF-related apoptosis-inducing ligand receptor (TRAIL-R)2. Addition of the 80-protein assay to established risk factors improved discrimination in the separate test sample from 0.686 (95% CI 0.682, 0.689) to 0.748 (95% CI 0.746, 0.751). A sparse model of 20 added proteins achieved a C statistic of 0.747 (95% CI 0.653, 0.842) in the test sample. Conclusions/interpretation We identified eight protein biomarkers, four of which are novel, for risk of MACE in community residents with type 2 diabetes, and found improved risk prediction by combining multiplex proteomics with an established risk model. Multiprotein arrays could be useful in identifying individuals with type 2 diabetes who are at highest risk of a cardiovascular event.

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  • 34.
    Rautiainen, Heidi
    et al.
    Swedish University of Agricultural Sciences, Uppsala.
    Alam, Moudud
    Dalarna University, School of Information and Engineering, Statistics.
    Blackwell, Paul G
    School of Mathematics & Statistics, University of Sheffield, Sheffield, UK.
    Skarin, Anna
    Swedish University of Agricultural Sciences, Uppsala.
    Identification of reindeer fine-scale foraging behaviour using tri-axial accelerometer data.2022In: Movement Ecology, E-ISSN 2051-3933, Vol. 10, no 1, article id 40Article in journal (Refereed)
    Abstract [en]

    Animal behavioural responses to the environment ultimately affect their survival. Monitoring animal fine-scale behaviour may improve understanding of animal functional response to the environment and provide an important indicator of the welfare of both wild and domesticated species. In this study, we illustrate the application of collar-attached acceleration sensors for investigating reindeer fine-scale behaviour. Using data from 19 reindeer, we tested the supervised machine learning algorithms Random forests, Support vector machines, and hidden Markov models to classify reindeer behaviour into seven classes: grazing, browsing low from shrubs or browsing high from trees, inactivity, walking, trotting, and other behaviours. We implemented leave-one-subject-out cross-validation to assess generalizable results on new individuals. Our main results illustrated that hidden Markov models were able to classify collar-attached accelerometer data into all our pre-defined behaviours of reindeer with reasonable accuracy while Random forests and Support vector machines were biased towards dominant classes. Random forests using 5-s windows had the highest overall accuracy (85%), while hidden Markov models were able to best predict individual behaviours and handle rare behaviours such as trotting and browsing high. We conclude that hidden Markov models provide a useful tool to remotely monitor reindeer and potentially other large herbivore species behaviour. These methods will allow us to quantify fine-scale behavioural processes in relation to environmental events.

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  • 35.
    Ren, Keni
    et al.
    Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Uppsala, Sweden.
    Alam, Moudud
    Dalarna University, School of Information and Engineering, Statistics.
    Nielsen, Per Peetz
    Department of Agriculture and Food, RISE Research Institutes of Sweden (RISE), Lund, Sweden.
    Gussmann, Maya
    Department of Veterinary and Animal Sciences, University of Copenhagen, Frederiksberg, Denmark.
    Rönnegård, Lars
    Dalarna University, School of Information and Engineering, Statistics. Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Uppsala, Sweden.
    Interpolation Methods to Improve Data Quality of Indoor Positioning Data for Dairy Cattle2022In: Frontiers in Animal Science, E-ISSN 2673-6225, Vol. 3, article id 896666Article in journal (Refereed)
    Abstract [en]

    Position data from real-time indoor positioning systems are increasingly used for studying individual cow behavior and social behavior in dairy herds. However, missing data challenges achieving reliable continuous activity monitoring and behavior studies. This study investigates the pattern of missing data and alternative interpolation methods in ultra-wideband based real-time indoor positioning systems in a free-stall barn. We collected 3 months of position data from a Swedish farm with around 200 cows. Data sampled for 6 days from 69 cows were used in subsequent analyzes to determine the location and duration of missing data. Data from 20 cows with the most reliable tags were selected to compare the effects of four different interpolation methods (previous, linear interpolation, cubic spline data interpolation and modified Akima interpolation). By comparing the observed data with the interpolations of the simulated missing data, the mean error distance varied from around 55 cm, using the previously last observed position, to around 17 cm for modified Akima. Modified Akima interpolation has the lowest error distance for all investigated activities (rest, walking, standing, feeding). Larger error distances were found in areas where the cows walk and turn, such as the corner between feeding and cubicles. Modified Akima interpolation is expected to be useful in the subsequent analyses of data gathered using real-time indoor positioning systems.

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  • 36.
    Ren, Keni
    et al.
    Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Uppsala, Sweden.
    Nielsen, Per Peetz
    Department of Agriculture and Food, RISE Research Institutes of Sweden, Lund, Sweden.
    Alam, Moudud
    Dalarna University, School of Information and Engineering, Statistics.
    Rönnegård, Lars
    Dalarna University, School of Information and Engineering, Statistics.
    Where do we find missing data in a commercial real-time location system? Evidence from 2 dairy farms2021In: JDS Communications, ISSN 2666-9102, Vol. 2, p. 345-350Article in journal (Refereed)
    Abstract [en]

    Real-time indoor positioning using ultra-wideband devices provides an opportunity for modern dairy farms to monitor the behavior of individual cows; however, missing data from these devices hinders reliable continuous monitoring and analysis of animal movement and social behavior. The objective of this study was to examine the data quality, in terms of missing data, in one commercially available ultra-wideband–based real-time location system for dairy cows. The focus was on detecting major obstacles, or sections, inside open freestall barns that resulted in increased levels of missing data. The study was conducted on 2 dairy farms with an existing commercial real-time location system. Position data were recorded for 6 full days from 69 cows on farm 1 and from 59 cows on farm 2. These data were used in subsequent analyses to determine the locations within the dairy barns where position data were missing for individual cows. The proportions of missing data were found to be evenly distributed within the 2 barns after fitting a linear mixed model with spatial smoothing to logit-transformed proportions (mean = 18% vs. 4% missing data for farm 1 and farm 2, respectively), with the exception of larger proportions of missing data along one of the walls on both farms. On farm 1, the variation between individual tags was large (range: 9–49%) compared with farm 2 (range: 12–38%). This greater individual variation of proportions of missing data indicates a potential problem with the individual tag, such as a battery malfunction or tag placement issue. Further research is needed to guide researchers in identifying problems relating to data capture problems in real-time monitoring systems on dairy farms. This is especially important when undertaking detailed analyses of animal movement and social interactions between animals.

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  • 37.
    Roos, Charlotte
    et al.
    Dalarna University, School of Health and Welfare, Caring Science/Nursing. Dalarna University, School of Health and Welfare, Care Sciences.
    Alam, Moudud
    Dalarna University, School of Information and Engineering, Statistics.
    Swall, Anna
    Dalarna University, School of Health and Welfare, Caring Science/Nursing.
    Boström, Anne-Marie
    Division of Nursing, Department of Neurobiology, Care Sciences and Society, Karolinska Institute, Stockholm, Sweden.
    Marmstål Hammar, Lena
    Dalarna University, School of Health and Welfare, Caring Science/Nursing. School of Health, Care and Social Welfare, Mälardalen University, Västerås, Sweden.
    Factors associated with older persons’ perceptions of dignity and well-being over a three-year period: A retrospective national study in residential care facilities2022In: BMC Geriatrics, ISSN 1471-2318, E-ISSN 1471-2318, Vol. 22, no 1, article id 515Article in journal (Refereed)
    Abstract [en]

    Background: Dignity and well-being are central concepts in the care of older people, 65 years and older, world‑wide. The person-centred practice framework identifes dignity and well-being as person-centred outcomes. Older persons living in residential care facilities, residents, have described that they sometimes lack a sense of dignity and well-being, and there is a need to understand which modifable factors to target to improve this. The aim of this study was to examine the associations between perceptions of dignity and wellbeing and the independent variables of the attitudes of staf, the indoor-outdoor-mealtime environments, and individual factors for residents over a three-year period.

    Methods: A national retrospective longitudinal mixed cohort study was conducted in all residential care facilities within 290 municipalities in Sweden. All residents aged 65 years and older in 2016, 2017 and 2018 were invited to responded to a survey; including questions regarding self-rated health and mobility, the attitudes of staf, the indooroutdoor-mealtime environments, safety, and social activities. Data regarding age, sex and diagnosed dementia/pre‑scribed medication for dementia were collected from two national databases. Descriptive statistics and ordinal logistic regression models were used to analyse the data.

    Results: A total of 13 763 (2016), 13 251 (2017) and 12 620 (2018) residents answered the survey. Most of them (69%) were women and the median age was 88 years. The odds for satisfaction with dignity did not difer over the three-year period, but the odds for satisfaction with well-being decreased over time. Residents who rated their health as good, who were not diagnosed with dementia/had no prescribed medication for dementia, who had not experienced disrespectful attitudes of staf and who found the indoor-outdoor-mealtime environments to be pleasant had higher odds of being satisfed with aspects of dignity and well-being over the three-year period.

    Conclusions: The person-centred practice framework, which targets the attitudes of staf and the care environment, can be used as a theoretical framework when designing improvement strategies to promote dignity and well-being. Registered nurses, due to their core competencies, focusing on person-centred care and quality improvement work, should be given an active role as facilitators in such improvement strategies.

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  • 38.
    Roos, Charlotte
    et al.
    Dalarna University, School of Health and Welfare, Care Sciences. Dalarna University, School of Health and Welfare, Caring Science/Nursing.
    Alam, Moudud
    Dalarna University, School of Information and Engineering, Statistics.
    Swall, Anna
    Dalarna University, School of Health and Welfare, Caring Science/Nursing.
    Boström, Anne‐Marie
    Division of Nursing Department of Neurobiology, Care Sciences and Society, Karolinska Institute, Stockholm, Sweden;Theme Inflammation and Ageing, Unit Nursing Ageing Karolinska University Hospital Huddinge Sweden;Research and Development UnitStockholms Sjukhem Stockholm Sweden.
    Marmstål Hammar, Lena
    Dalarna University, School of Health and Welfare, Caring Science/Nursing. Division of Nursing, Department of Neurobiology, Care Sciences and Society, Karolinska Institute, Stockholm, Sweden; School of Health, Care and Social Welfare, Mälardalen University, Västerås, Sweden.
    Factors associated with perceptions of dignity and well‐being among older people living in residential care facilities in Sweden. A national cross‐sectional study2022In: Health & Social Care in the Community, ISSN 0966-0410, E-ISSN 1365-2524, Vol. 30, no 5, p. e2350-e2364Article in journal (Refereed)
    Abstract [en]

    The care of older people living in residential care facilities (RCFs) should promote dignity and well-being, but research shows that these aspects are lacking in such facilities. To promote dignity and well-being, it is important to understand which associated factors to target. The aim of this study was to examine the associations between perceived dignity and well-being and factors related to the attitudes of staff, the care environment and individual issues among older people living in RCFs. A national retrospective cross-sectional study was conducted in all RCFs for older people within 290 municipalities in Sweden. All older people 65 years and older (n = 71,696) living in RCFs in 2018 were invited to respond to the survey. The response rate was 49%. The survey included the following areas: self-rated health, indoor-outdoor-mealtime environment, performance of care, attitudes of staff, safety, social activities, availability of staff and care in its entirety. Data were supplemented with additional data from two national databases regarding age, sex and diagnosed dementia. Descriptive statistics and ordinal logistic regression models were used to analyse the data. Respondents who had experienced disrespectful treatment, those who did not thrive in the indoor-outdoor-mealtime environment, those who rated their health as poor and those with dementia had higher odds of being dissatisfied with dignity and well-being. To promote dignity and well-being, there is a need to improve the prerequisites of staff regarding respectful attitudes and to improve the care environment. The person-centred practice framework can be used as a theoretical framework for improvements, as it targets the prerequisites of staff and the care environment. As dignity and well-being are central values in the care of older people worldwide, the results of this study can be generalised to other care settings for older people in countries outside of Sweden.

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  • 39.
    Rönnegård, Lars
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Shen, Xia
    Dalarna University, School of Technology and Business Studies, Statistics.
    Alam, Moudud
    Dalarna University, School of Technology and Business Studies, Statistics.
    Hglm: A package for fitting hierarchical generalized linear models2010In: The R Journal, E-ISSN 2073-4859, Vol. 2, no 2, p. 20-28Article in journal (Refereed)
    Abstract [en]

    We present the hglm package for fitting hierarchical generalized linear models. It can be used for linear mixed models and generalized linear mixed models with random effects for a variety of links and a variety of distributions for both the outcomes and the random effects. Fixed effects can also be fitted in the dispersion part of the model.

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  • 40.
    Saeed, Nausheen
    et al.
    Dalarna University, School of Information and Engineering, Microdata Analysis.
    Alam, Moudud
    Dalarna University, School of Information and Engineering, Statistics.
    Nyberg, Roger G.
    Dalarna University, School of Information and Engineering, Informatics.
    A multimodal deep learning approach for gravel road condition evaluation through image and audio integration2024In: Transportation Engineering, ISSN 2666-691X, Vol. 16, article id 100228Article in journal (Refereed)
    Abstract [en]

    This study investigates the combination of audio and image data to classify road conditions, particularly focusingon loose gravel scenarios. The dataset underwent binary categorisation, comprising audio segments capturinggravel sounds and corresponding images. Early feature fusion, utilising a pre-trained Very Deep ConvolutionalNetworks 19 (VGG19) and Principal component analysis (PCA), improved the accuracy of the Random Forestclassifier, surpassing other models in accuracy, precision, recall, and F1-score. Late fusion, involving decisionlevelprocessing with logical disjunction and conjunction gates (AND and OR) in combination with individualclassifiers for images and audio based on Densely Connected Convolutional Networks 121 (DenseNet121),demonstrated notable performance, especially with the OR gate, achieving 97 % accuracy. The late fusionmethod enhances adaptability by compensating for limitations in one modality with information from the other.Adapting maintenance based on identified road conditions minimises unnecessary environmental impact. Thismethod can help to identify loose gravel on gravel roads, substantially improving road safety and implementing aprecise maintenance strategy through a data-driven approach.

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  • 41.
    Saeed, Nausheen
    et al.
    Dalarna University, School of Technology and Business Studies, Microdata Analysis.
    Alam, Moudud
    Dalarna University, School of Technology and Business Studies, Statistics.
    Nyberg, Roger G.
    Dalarna University, School of Technology and Business Studies, Information Systems.
    Dougherty, Mark
    Halmstad University.
    Rebreyend, Pascal
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Jomaa, Diala
    Dalarna University, School of Technology and Business Studies, Microdata Analysis.
    Comparison of Pattern Recognition Techniques for Classification of the Acoustics of Loose Gravel2020In: 2020 7th International Conference on Soft Computing and Machine Intelligence, ISCMI 2020, 2020, p. 237-243, article id 9311569Conference paper (Refereed)
    Abstract [en]

    Road condition evaluation is a critical part of gravel road maintenance. One of the parameters that are assessed is loose Gravel. An expert does this evaluation by subjectively looking at images taken and written text for deciding on the road condition. This method is labor-intensive and subjected to an error of judgment; therefore, it is not reliable. Road management agencies are looking for more efficient and automated objective measurement methods. In this study, acoustic data of gravel hitting the bottom of the car is used, and the relation between these acoustics and the condition of loose gravel on gravel roads is seen. A novel acoustic classification method based on Ensemble bagged tree (EBT) algorithm is proposed in this study for the classification of loose gravel sounds. The accuracy of the EBT algorithm for Gravel and Non-gravel sound classification is found to be 97.5. The detection of the negative classes, i.e., non-gravel detection, is preeminent, which is considerably higher than Boosted Trees, RUSBoosted Tree, Support vector machines (SVM), and decision trees.

  • 42.
    Saeed, Nausheen
    et al.
    Dalarna University, School of Information and Engineering, Microdata Analysis.
    Nyberg, Roger G.
    Dalarna University, School of Information and Engineering, Informatics.
    Alam, Moudud
    Dalarna University, School of Information and Engineering, Statistics.
    Gravel road classification based on loose gravel using transfer learning2022In: The international journal of pavement engineering, ISSN 1029-8436, E-ISSN 1477-268X, p. 1-8Article in journal (Refereed)
    Abstract [en]

    Road maintenance agencies subjectively assess loose gravel as one of the parameters for determininggravel road conditions. This study aims to evaluate the performance of deep learning-based pretrainednetworks in rating gravel road images according to classical methods as done by humanexperts. The dataset consists of images of gravel roads extracted from self-recorded videos andimages extracted from Google Street View. The images were labelled manually, referring to thestandard images as ground truth defined by the Road Maintenance Agency in Sweden (Trafikverket).The dataset was then partitioned in a ratio of 60:40 for training and testing. Various pre-trainedmodels for computer vision tasks, namely Resnet18, Resnet50, Alexnet, DenseNet121, DenseNet201,and VGG-16, were used in the present study. The last few layers of these models were replaced toaccommodate new image categories for our application. All the models performed well, with anaccuracy of over 92%. The results reveal that the pre-trained VGG-16 with transfer learning exhibitedthe best performance in terms of accuracy and F1-score compared to other proposed models.

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  • 43.
    Saeed, Nausheen
    et al.
    Dalarna University, School of Information and Engineering, Microdata Analysis.
    Nyberg, Roger G.
    Dalarna University, School of Information and Engineering, Informatics.
    Alam, Moudud
    Dalarna University, School of Information and Engineering, Statistics.
    Dougherty, Mark
    School of Information Technology, Halmstad University.
    Jomaa, Diala
    Dalarna University, School of Teacher Education, Education.
    Rebreyend, Pascal
    Dalarna University, School of Information and Engineering, Computer Engineering.
    Classification of the Acoustics of Loose Gravel2021In: Sensors, E-ISSN 1424-8220, Vol. 21, no 14, article id 4944Article in journal (Refereed)
    Abstract [en]

    Road condition evaluation is a critical part of gravel road maintenance. One of the assessed parameters is the amount of loose gravel, as this determines the driving quality and safety. Loose gravel can cause tires to slip and the driver to lose control. An expert assesses the road conditions subjectively by looking at images and notes. This method is labor-intensive and subject to error in judgment; therefore, its reliability is questionable. Road management agencies look for automated and objective measurement systems. In this study, acoustic data on gravel hitting the bottom of a car was used. The connection between the acoustics and the condition of loose gravel on gravel roads was assessed. Traditional supervised learning algorithms and convolution neural network (CNN) were applied, and their performances are compared for the classification of loose gravel acoustics. The advantage of using a pre-trained CNN is that it selects relevant features for training. In addition, pre-trained networks offer the advantage of not requiring days of training or colossal training data. In supervised learning, the accuracy of the ensemble bagged tree algorithm for gravel and non-gravel sound classification was found to be 97.5%, whereas, in the case of deep learning, pre-trained network GoogLeNet accuracy was 97.91% for classifying spectrogram images of the gravel sounds.

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    Classification of the Acoustics of Loose Gravel
  • 44.
    Saleh, Roxan
    et al.
    Dalarna University, School of Information and Engineering, Microdata Analysis. Swedish Transport Administration, Borlänge.
    Fleyeh, Hasan
    Dalarna University, School of Information and Engineering, Computer Engineering.
    Alam, Moudud
    Dalarna University, School of Information and Engineering, Statistics.
    An Analysis of the Factors Influencing the Retroreflectivity Performance of In-Service Road Traffic Signs2022In: Applied Sciences, E-ISSN 2076-3417, Vol. 12, no 5, article id 2413Article in journal (Refereed)
    Abstract [en]

    The road traffic signs in Sweden have no inventory system and it is unknown when a sign has reached the end of its service life and needs to be replaced. As a result, the road authorities do not have a systematic maintenance program for road traffic signs, and many signs which are not in compliance with the minimum retroreflectivity performance requirements are still found on the roads. Therefore, it is very important to find an inexpensive, safe, easy, and highly accurate method to judge the retroreflectivity performance of road signs. This will enable maintenance staff to determine the retroreflectivity of road signs without requiring measuring instruments for retroreflectivity or colors performance. As a first step toward the above goal, this paper aims to identify factors affecting the retroreflectivity of road signs. Two different datasets were used, namely, the VTI dataset from Sweden and NMF dataset from Denmark. After testing different models, two logarithmic regression models were found to be the best-fitting models, with R2 values of 0.50 and 0.95 for the VTI and NMF datasets, respectively. The first model identified the age, direction, GPS positions, color, and class of road signs as significant predictors, while the second model used age, color, and the class of road signs. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.

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  • 45.
    Saleh, Roxan
    et al.
    Dalarna University, School of Information and Engineering, Microdata Analysis. Swedish Transport Administration,Borlänge.
    Fleyeh, Hasan
    Dalarna University, School of Information and Engineering, Computer Engineering.
    Alam, Moudud
    Dalarna University, School of Information and Engineering, Statistics.
    Hintze, Arend
    Dalarna University, School of Information and Engineering, Microdata Analysis.
    Assessing the color status and daylight chromaticity of road signs through machine learning approaches2023In: IATSS Research, ISSN 0386-1112, Vol. 47, no 3, p. 305-317Article in journal (Refereed)
    Abstract [en]

    The color of road signs is a critical aspect of road safety, as it helps drivers quickly and accurately identify and respond to these signs. Properly colored road signs improve visibility during the day and make it easier for drivers to make informed decisions while driving. In order to ensure the safety and efficiency of road traffic, it is essential to maintain the appropriate color level of road signs. The objective of this study was to analyze the color status and daylight chromaticity of in-use road signs using supervised machine learning models, and to explore the correlation between road sign's age and daylight chromaticity. Three algorithms were employed: Random Forest (RF), Support Vector Machine (SVM), and Artificial Neural Network (ANN). The data used in this study was collected from road signs that were in-use on roads in Sweden. The study employed classification models to assess the color status (accepted or rejected) of the road signs based on minimum acceptable color levels according to standards, and regression models to predict the daylight chromaticity values. The correlation between road sign's age and daylight chromaticity was explored through regression analysis. Daylight chromaticity describes the color quality of road signs in daylight, that is expressed in terms of X and Y chromaticity coordinates. The study revealed a linear relationship between the road sign's age and daylight chromaticity for blue, green, red, and white sheeting, but not for yellow. The lifespan of red signs was estimated to be around 12 years, much shorter than the estimated lifespans of yellow, green, blue, and white sheeting, which are 35, 42, 45, and 75 years, respectively. The supervised machine learning models successfully assessed the color status of the road signs and predicted the daylight chromaticity values using the three algorithms. The results of this study showed that the ANN classification and ANN regression models achieved high accuracy of 81% and R2 of 97%, respectively. The RF and SVM models also performed well, with accuracy values of 74% and 79% and R2 ranging from 59% to 92%. The findings demonstrate the potential of machine learning to effectively predict the status and daylight chromaticity of road signs and their impact on road safety in the Swedish context. © 2023 International Association of Traffic and Safety Sciences

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  • 46.
    Saqlain, Murshid
    et al.
    Dalarna University, School of Technology and Business Studies, Microdata Analysis.
    Alam, Moudud
    Dalarna University, School of Technology and Business Studies, Statistics.
    Brandt, Daniel
    Dalarna University, School of Technology and Business Studies, Human Geography.
    Rönnegård, Lars
    Dalarna University, School of Technology and Business Studies, Statistics.
    Westin, Jerker
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Stochastic differential equations modelling of levodopa concentration in patients with Parkinson's disease2018Conference paper (Other academic)
    Abstract [en]

    The purpose of this study is to investigate a pharmacokinetic model of levodopa concentration in patients with Parkinson's disease by introducing stochasticity so that inter-individual variability may be separated into measurement and system noise. It also aims to investigate whether the stochastic differential equations (SDE) model provide better fits than its ordinary differential equations (ODE) counterpart, by using a real data set. Westin et al. developed a pharmacokinetic-pharmacodynamic model for duodenal levodopa infusion described by four ODEs, the first three of which define the pharmacokinetic model. In this study, system noise variables are added to the aforementioned first three equations through a standard Wiener process, also known as Brownian motion. The R package PSM for mixed-effects models is used on data from previous studies for modelling levodopa concentration and parameter estimation. First, the diffusion scale parameter, σ, and bioavailability are estimated with the SDE model. Second, σ is fixed to integer values between 1 and 5, and bioavailability is estimated. Cross-validation is performed to determine whether the SDE based model explains the observed data better or not by comparingthe average root mean squared errors (RMSE) of predicted levodopa concentration. Both ODE and SDE models estimated bioavailability to be about 88%. The SDE model converged at different values of σ that were signicantly different from zero while estimating bioavailability to be about 88%. The average RMSE for the ODE model wasfound to be 0.2980, and the lowest average RMSE for the SDE model was 0.2748 when σ was xed to 4. Both models estimated similar values for bioavailability, and the non-zero σ estimate implies that the inter-individual variability may be separated. However, the improvement in the predictive performance of the SDE model turned out to be rather small, compared to the ODE model.

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  • 47.
    Saqlain, Murshid
    et al.
    Dalarna University, School of Technology and Business Studies, Microdata Analysis.
    Alam, Moudud
    Dalarna University, School of Technology and Business Studies, Statistics.
    Rönnegård, Lars
    Dalarna University, School of Technology and Business Studies, Statistics.
    Westin, Jerker
    Dalarna University, School of Technology and Business Studies, Computer Engineering.
    Investigating Stochastic Differential Equations Modelling for Levodopa Infusion in Patients with Parkinson's Disease2020In: European journal of drug metabolism and pharmacokinetics, ISSN 0378-7966, E-ISSN 2107-0180, Vol. 45, no 1, p. 41-49Article in journal (Refereed)
    Abstract [en]

    BACKGROUND AND OBJECTIVES: Levodopa concentration in patients with Parkinson's disease is frequently modelled with ordinary differential equations (ODEs). Here, we investigate a pharmacokinetic model of plasma levodopa concentration in patients with Parkinson's disease by introducing stochasticity to separate the intra-individual variability into measurement and system noise, and to account for auto-correlated errors. We also investigate whether the induced stochasticity provides a better fit than the ODE approach.

    METHODS: In this study, a system noise variable is added to the pharmacokinetic model for duodenal levodopa/carbidopa gel (LCIG) infusion described by three ODEs through a standard Wiener process, leading to a stochastic differential equations (SDE) model. The R package population stochastic modelling (PSM) was used for model fitting with data from previous studies for modelling plasma levodopa concentration and parameter estimation. First, the diffusion scale parameter (σw), measurement noise variance, and bioavailability are estimated with the SDE model. Second, σw is fixed to certain values from 0 to 1 and bioavailability is estimated. Cross-validation was performed to compare the average root mean square errors (RMSE) of predicted plasma levodopa concentration.

    RESULTS: Both the ODE and the SDE models estimated bioavailability to be approximately 75%. The SDE model converged at different values of σw that were significantly different from zero. The average RMSE for the ODE model was 0.313, and the lowest average RMSE for the SDE model was 0.297 when σw was fixed to 0.9, and these two values are significantly different.

    CONCLUSIONS: The SDE model provided a better fit for LCIG plasma levodopa concentration by approximately 5.5% in terms of mean percentage change of RMSE.

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  • 48.
    Shen, Xia
    et al.
    Dalarna University, School of Technology and Business Studies, Statistics.
    Alam, Moudud
    Dalarna University, School of Technology and Business Studies, Statistics.
    Fikse, Freddy
    Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Uppsala.
    Rönnegård, Lars
    Dalarna University, School of Technology and Business Studies, Statistics.
    A novel generalized ridge regression method for quantitative genetics2013In: Genetics, ISSN 0016-6731, E-ISSN 1943-2631, Vol. 193, no 4, p. 1255-1268Article in journal (Refereed)
    Abstract [en]

    As the molecular marker density grows, there is a strong need in both genome-wide association studies and genomic selection to fit models with a large number of parameters. Here we present a computationally efficient generalized ridge regression (RR) algorithmfor situations where the number of parameters largely exceeds the number of observations. The computationally demanding parts of the method depend mainly on the number ofobservations and not the number of parameters. The algorithm was implemented in the R package bigRR based on the previously developed package hglm. Using such an approach, a heteroscedastic effects model (HEM) was also developed, implemented and tested. Theefficiency for different data sizes were evaluated via simulation. The method was tested for a bacteria-hypersensitive trait in a publicly available Arabidopsis dataset including 84 inbred lines and 216 130 SNPs. The computation of all the SNP effects required less than10 seconds using a single 2.7 GHz core. The advantage in run-time makes permutationtest feasible for such a whole-genome model, so that a genome-wide significance threshold can be obtained. HEM was found to be more robust than ordinary RR (a.k.a. SNPBLUP) in terms of QTL mapping, because SNP specific shrinkage was applied instead of acommon shrinkage. The proposed algorithm was also assessed for genomic evaluation and was shown to give better predictions than ordinary RR.

  • 49. Skarin, A.
    et al.
    Alam, Moudud
    Dalarna University, School of Technology and Business Studies, Statistics.
    Reindeer habitat use in relation to two small wind farms, during preconstruction, construction, and operation2017In: Ecology and Evolution, E-ISSN 2045-7758, Vol. 7, no 11, p. 3870-3882Article in journal (Refereed)
    Abstract [en]

    Worldwide there is a rush toward wind power development and its associated infrastructure. In Fennoscandia, large-scale wind farms comprising several hundred windmills are currently built in important grazing ranges used for Sámi reindeer husbandry. In this study, reindeer habitat use was assessed using reindeer fecal pellet group counts in relation to two relatively small wind farms, with 8 and 10 turbines, respectively. In 2009, 1,315 15-m2 plots were established and pellet groups were counted and cleaned from the plots. This was repeated once a year in May, during preconstruction, construction, and operation of the wind farms, covering 6 years (2009-2014) of reindeer habitat use in the area. We modeled the presence/absence of any pellets in a plot at both the local (wind farm site) and regional (reindeer calving to autumn range) scale with a hierarchical logistic regression, where spatial correlation was accounted for via random effects, using vegetation type, and the interaction between distance to wind turbine and time period as predictor variables. Our results revealed an absolute reduction in pellet groups by 66% and 86% around each wind farm, respectively, at local scale and by 61% at regional scale during the operation phase compared to the preconstruction phase. At the regional, scale habitat use declined close to the turbines in the same comparison. However, at the local scale, we observed increased habitat use close to the wind turbines at one of the wind farms during the operation phase. This may be explained by continued use of an important migration route close to the wind farm. The reduced use at the regional scale nevertheless suggests that there may be an overall avoidance of both wind farms during operation, but further studies of reindeer movement and behavior are needed to gain a better understanding of the mechanisms behind this suggested avoidance.

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  • 50.
    Skarin, Anna
    et al.
    SLU.
    Sandström, Per
    SLU.
    Alam, Moudud
    Dalarna University, School of Technology and Business Studies, Statistics.
    Out of sight of wind turbines — Reindeer response to wind farms in operation2018In: Ecology and Evolution, E-ISSN 2045-7758, Vol. 8, p. 9906-9919Article in journal (Refereed)
    Abstract [en]

    To meet the expanding land use required for wind energy development, a better understanding of the effects on terrestrial animals’ responses to such development is required. Using GPS-data from 50 freely ranging female reindeer (Rangifer tarandus) in the Malå reindeer herding community, Sweden, we determined reindeer calving sites and estimated reindeer habitat selection using resource selection functions (RSF). RSFs were estimated at both second- (selection of home range) and third-order (selection within home range) scale in relation to environmental variables, wind farm (WF) development phase (before construction, construction, and operation), distance to the WFs and at the second-order scale whether the wind turbines were in or out of sight of the reindeer. We found that the distance between reindeer calving site and WFs increased during the operation phase, compared to before construction. At both scales of selection, we found a significant decrease in habitat selection of areas in proximity of the WFs, in the same comparison. The results also revealed a shift in home range selection away from habitats where wind turbines became visible toward habitats where the wind turbines were obscured by topography (increase in use by 79% at 5 km). We interpret the reindeer shift in home range selection as an effect of the wind turbines per se. Using topography and land cover information together with the positions of wind turbines could therefore help identify sensitive habitats for reindeer and improve the planning and placement of WFs. In addition, we found that operation phase of these WFs had a stronger adverse impact on reindeer habitat selection than the construction phase. Thus, the continuous running of the wind turbines making a sound both day and night seemed to have disturbed the reindeer more than the sudden sounds and increased human activity during construction work.

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