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  • 1.
    Gundy, Richard
    et al.
    Rutgers University.
    Jonsson, Adam
    Scaling Functions on R2 for Dilations with Determinant ±22010In: Applied and Computational Harmonic Analysis, ISSN 1063-5203, E-ISSN 1096-603X, Vol. 29, no 1, p. 49-62Article in journal (Refereed)
    Abstract [en]

    This paper gives necessary and sufficient conditions for a doubly periodic function p(ξ ), ξ ∈ R2, to be the squared modulus of a lowpass filter for a multiresolution analysis of L2(R2) with respect to an expanding matrix A of determinant ±2. By transferring the underlying spaces, R or R2, to a single binary sequence space, we are able to show that, when det(A) = 2, every scaling function on R2 corresponds to one on R, where the dilation is ±2. If det(A)=−2, this is no longer true. In this case, the lowpass filter for the stretched Haar function makes an unexpected appearance.

  • 2.
    Hamodi, Hussan
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Lundberg, Jan
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Jonsson, Adam
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Mathematical Science.
    Economic lifetime of a drilling machine: a case study on mining industry2015In: International Journal of Strategic Engineering Asset Management (IJSEAM), ISSN 1759-9733, E-ISSN 1759-9741, Vol. 2, no 2, p. 177-189Article in journal (Refereed)
    Abstract [en]

    Underground mines use many different types of machinery duringthe drift mining processes of drilling, charging, blasting, loading, scaling andbolting. Drilling machines play a critical role in the mineral extraction processand thus are important economically. However, as the machines age, theirefficiency and effectiveness decrease, negatively affecting productivity andprofitability and increasing total cost. Hence, the economic replacementlifetime of the machine is a key performance indicator. This paper introducesan optimisation model that gives the optimal lifetime for a drilling machine. Acase study has been done at an underground Swedish mine to identify theeconomic replacement time of a drilling machine. It considers the purchaseprice, maintenance and operation costs, and the machine’s second-hand value.Findings show that the economic replacement lifetime of a drilling machine inthis mine is 96 months. The proposed model can be used for other undergroundmining machines.

  • 3.
    Hamodi, Hussan
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Lundberg, Jan
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Jonsson, Adam
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Mathematical Science.
    Economic lifetime of a drilling machine: a case study on mining industry2013In: MPMM 2013 (Maintenance Performance Measurement and Management) / [ed] sari Monto; Miia Pirttilä; Timo Kärri, Lappeenranta, Finland: MPMM 2013 , 2013, p. 138-147Conference paper (Refereed)
    Abstract [en]

    Underground mines use many different types of machinery during the drift mining processesof drilling, charging, blasting, loading, scaling and bolting. Drilling machines play a criticalrole in the mineral extraction process and thus are important economically. However, as themachines age, their efficiency and effectiveness decrease, negatively affecting productivityand profitability and increasing total cost. Hence, the economic replacement lifetime of themachine is a key performance indicator. This paper introduces an optimisation model thatgives the optimal lifetime for a drilling machine. A case study has been done at anunderground Swedish mine to identify the economic replacement time of a drilling machine.It considers the purchase price, maintenance and operation costs, and the machine’s secondhandvalue. Findings show that the economic replacement lifetime of a drilling machine inthis mine is 96 months. The proposed model can be used for other underground miningmachines.

  • 4.
    Hamodi, Hussan
    et al.
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Lundberg, Jan
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Jonsson, Adam
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Mathematical Science.
    Ahmadi, Alireza
    Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Operation, Maintenance and Acoustics.
    Case Study: Model for economic lifetime of drilling machines in the Swedish mining industry2015In: The Engineering Economist, ISSN 0013-791X, E-ISSN 1547-2701, Vol. 60, no 2, p. 138-154Article in journal (Refereed)
    Abstract [en]

    The purpose of this paper is to develop a practical economic replacement decision model to identify the economic lifetime of a mining drilling machine. A data driven optimisation model was developed for operating and maintenance costs, purchase price and machine resale value. Equivalent present value of these costs by using discount rate was considered. The proposed model shows that the absolute optimal replacement time (ORT) of a drilling machine used in one underground mine in Sweden is 115 months. Sensitivity and regression analysis show that the maintenance cost has the largest impact on the ORT of this machine. The proposed decision making model is applicable and useful and can be implemented within the mining industry.

  • 5.
    Jonsson, Adam
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Mathematical Science.
    Invariant sets for QMF functions2018In: Rocky Mountain Journal of Mathematics, ISSN 0035-7596, E-ISSN 1945-3795, Vol. 48, no 8, p. 2559-2571Article in journal (Refereed)
    Abstract [en]

    A quadrature mirror filter (QMF) function can be considered as the transition function for a Markov process on the unit interval. The QMF functions that generate scaling functions for multiresolution analyses are then distinguished by properties of their invariant sets. By characterizing these sets, we answer in the affirmative a question raised by Gundy.

  • 6.
    Jonsson, Adam
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Mathematical Science.
    On g-functions for countable state subshifts2017In: Archiv der Mathematik, ISSN 0003-889X, E-ISSN 1420-8938, Vol. 109, no 4, p. 373-381Article in journal (Refereed)
    Abstract [en]

    This note revisits the problem of finding necessary and sufficient conditions for a subshift to admit a continuous g-function. Results obtained by Krieger (in: IMS lecture notes monograph series, vol 48, pp 306-316, 2006) on finite alphabet subshifts are generalized to countable state subshifts.

  • 7.
    Jonsson, Adam
    et al.
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Mathematical Science.
    Voorneveld, Mark
    Department of Economics, Stockholm School of Economics.
    The limit of discounted utilitarianism2018In: Theoretical Economics, ISSN 1933-6837, E-ISSN 1555-7561, Vol. 13, no 1, p. 19-37Article in journal (Refereed)
    Abstract [en]

    This paper presents an infinite-horizon version of intergenerational utilitarianism. By studying discounted utilitarianism as the discount factor tends to one, we obtain a new welfare criterion: limit-discounted utilitarianism (LDU). We show that LDU meets the standard assumptions of efficiency, equity, and interpersonal comparability, but allows us to compare more pairs of utility streams than commonly-used utilitarian criteria, including the overtaking criterion and the catching-up criterion. We also introduce a principle of compensation for postponements of utility streams and use it to characterize the LDU criterion on a restricted domain.

  • 8.
    Jonsson, Adam
    et al.
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Mathematical Science.
    Voorneveld, Mark
    Stockholm School of Economics.
    Utilitarianism on infinite utility streams: summable differences and finite averages2015In: Economic Theory Bulletin, ISSN 2196-1085, E-ISSN 2196-1093, Vol. 3, no 1, p. 19-31Article in journal (Refereed)
    Abstract [en]

    This paper provides axiomatic descriptions of social welfare relations, defined on infinite streams of utility, that are consistent with the utilitarian criterion on subsets where maximizing aggregate utility has a clear interpretation: the streams, or their differences, are summable. Besides standard assumptions on efficiency, equity and interpersonal comparability, two axioms are introduced and shown to be necessary and sufficient. A more general version of one axiom suffices to distinguish streams with different long-run averages.

  • 9.
    Martinsson, Jesper
    et al.
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Mathematical Science. Department of Mining Technology, Luossavaara-Kiirunavaara AB, 98381 Malmberget.
    Jonsson, Adam
    Luleå University of Technology, Department of Engineering Sciences and Mathematics, Mathematical Science.
    A New Model for the Distribution of Observable Earthquake Magnitudes and Applications to b-Value Estimation2018In: IEEE Geoscience and Remote Sensing Letters, ISSN 1545-598X, E-ISSN 1558-0571, Vol. 15, no 6, p. 833-837Article in journal (Refereed)
    Abstract [en]

    The b-value in the Gutenberg–Richter (GR) law contains information that is essential for evaluating earthquake hazard and predicting the occurrence of large earthquakes. Estimates of b are often based on seismic events whose magnitude exceed a certain threshold, the so-called magnitude of completeness. Such estimates are sensitive to the choice of threshold and often ignore a substantial portion of available data. We present a general model for the distribution of observable earthquake magnitudes and an estimation procedure that takes all measurements into account. The model is obtained by generalizing previous probabilistic descriptions of sensor network limitations and using a generalization of the GR law. We show that our model is flexible enough to handle spatio-temporal variations in the seismic environment and captures valuable information about sensor network coverage. We also show that the model leads to significantly improved b-value estimates compared with established methods relying on the magnitude of completeness.

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