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Träfflista för sökning "WFRF:(Ali A) ;lar1:(kau)"

Sökning: WFRF:(Ali A) > Karlstads universitet

  • Resultat 1-9 av 9
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1.
  • Kattge, Jens, et al. (författare)
  • TRY plant trait database - enhanced coverage and open access
  • 2020
  • Ingår i: Global Change Biology. - : Wiley-Blackwell. - 1354-1013 .- 1365-2486. ; 26:1, s. 119-188
  • Tidskriftsartikel (refereegranskat)abstract
    • Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives.
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2.
  • Rabiee, Navid, et al. (författare)
  • Green Biomaterials : fundamental principles
  • 2023
  • Ingår i: Green Biomaterials. - : Taylor & Francis. - 2993-4168. ; 1:1, s. 1-4
  • Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)
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3.
  • Rafique, Asia, et al. (författare)
  • Design and Modeling of a Fuel Cell System Using Biomass Feedstock as a Biofuel
  • 2020
  • Ingår i: Fuel Cells. - : Wiley. - 1615-6846 .- 1615-6854. ; 20:1, s. 89-97
  • Tidskriftsartikel (refereegranskat)abstract
    • This paper aims to model ceramic fuel cell system based on low-temperature planar solid oxide fuel cell (SOFC) different biogases fuels from multiple biomasses, that is, animal waste, redwood, rice husk and sugar cane. Biomass is a better choice for the generation of energy globally. Therefore, there is a focus on the most available biomass resources in the country that can be used as clean energy sources. This developed model is designed by thermodynamic analysis and electrochemical calculations using MATLAB. The designed model is a lumped parameter model based on the steady-state one-dimensional flow. In this model, all calculated power and flow rate values were kept as positive values. Also, the system is considered to be free of leaks, and heat loss is neglected. The operating temperature and pressure are assumed to be 500–700 °C and the partial pressure is set at three different pressures; P1 (1 bar), P2 (2 bar), and P3 (3 bar), respectively, and fuel utilization factor is 80%. It is observed that the best performance is obtained with animal-waste based biogas at 700 °C and P3 (3 bar).
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4.
  • Ahmad, Iftikhar, et al. (författare)
  • Using algorithmic trading to analyze short term profitability of Bitcoin
  • 2021
  • Ingår i: PeerJ Computer Science. - : PeerJ Publishing. - 2376-5992. ; 7
  • Tidskriftsartikel (refereegranskat)abstract
    • Cryptocurrencies such as Bitcoin (BTC) have seen a surge in value in the recent past and appeared as a useful investment opportunity for traders. However, their short term profitability using algorithmic trading strategies remains unanswered. In this work, we focus on the short term profitability of BTC against the euro and the yen for an eight-year period using seven trading algorithms over trading periods of length 15 and 30 days. We use the classical buy and hold (BH) as a benchmark strategy. Rather surprisingly, we found that on average, the yen is more profitable than BTC and the euro; however the answer also depends on the choice of algorithm. Reservation price algorithms result in 7.5% and 10% of average returns over 15 and 30 days respectively which is the highest for all the algorithms for the three assets. For BTC, all algorithms outperform the BH strategy. We also analyze the effect of transaction fee on the profitability of algorithms for BTC and observe that for trading period of length 15 no trading strategy is profitable for BTC. For trading period of length 30, only two strategies are profitable. 
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5.
  • Ali, Asad A., et al. (författare)
  • On the stability and convergence of a sliding-window variable-regularization recursive-least-squares algorithm
  • 2016
  • Ingår i: International journal of adaptive control and signal processing (Print). - : John Wiley & Sons. - 0890-6327 .- 1099-1115. ; 30:5, s. 715-735
  • Tidskriftsartikel (refereegranskat)abstract
    • A sliding-window variable-regularization recursive-least-squares algorithm is derived, and its convergence properties, computational complexity, and numerical stability are analyzed. The algorithm operates on a finite data window and allows for time-varying regularization in the weighting and the difference between estimates. Numerical examples are provided to compare the performance of this technique with the least mean squares and affine projection algorithms. Copyright (c) 2015 John Wiley & Sons, Ltd.
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7.
  • Krzywda, Jakub, 1989-, et al. (författare)
  • ALPACA : Application Performance Aware Server Power Capping
  • 2018
  • Ingår i: ICAC 2018. - : IEEE Computer Society. - 9781538651391 ; , s. 41-50
  • Konferensbidrag (refereegranskat)abstract
    • Server power capping limits the power consumption of a server to not exceed a specific power budget. This allows data center operators to reduce the peak power consumption at the cost of performance degradation of hosted applications. Previous work on server power capping rarely considers Quality-of-Service (QoS) requirements of consolidated services when enforcing the power budget. In this paper, we introduce ALPACA, a framework to reduce QoS violations and overall application performance degradation for consolidated services. ALPACA reduces unnecessary high power consumption when there is no performance gain, and divides the power among the running services in a way that reduces the overall QoS degradation when the power is scarce. We evaluate ALPACA using four applications: MediaWiki, SysBench, Sock Shop, and CloudSuite’s Web Search benchmark. Our experiments show that ALPACA reduces the operational costs of QoS penalties and electricity by up to 40% compared to a non optimized system. 
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8.
  • Naqvi, Salman Raza, et al. (författare)
  • Pyrolysis of high ash sewage sludge : Kinetics and thermodynamic analysis using Coats-Redfern method
  • 2019
  • Ingår i: Renewable energy. - : Elsevier Ltd. - 0960-1481 .- 1879-0682. ; 131, s. 854-860
  • Tidskriftsartikel (refereegranskat)abstract
    • This study aims to investigate the thermo-kinetics of high-ash sewage sludge using thermogravimetric analysis. Sewage sludge was dried, pulverized and heated non-isothermally from 25 to 800 °C at different heating rates (5, 10 and 20 °C/min) in N2 atmosphere. TG and DTG results indicate that the sewage sludge pyrolysis may be divided into three stages. Coats-Redfern integral method was applied in the 2nd and 3rd stage to estimate the activation energy and pre-exponential factor from mass loss data using five major reaction mechanisms. The low-temperature stable components (LTSC) of the sewage sludge degraded in the temperature regime of 250–450 °C while high-temperature stable components (HTSC) decomposed in the temperature range of 450–700 °C. According to the results, first-order reaction model (F1) showed higher Ea with better R2 for all heating rates. D3, N1, and S1 produced higher Ea at higher heating rates for LTSC pyrolysis and lower Ea with the increase of heating rates for HTSC pyrolysis. All models showed positive ΔH except F1.5. Among all models, Diffusion (D1, D2, D3) and phase interfacial models (S1, S2) showed higher ΔG as compared to reaction, nucleation, and power-law models in section I and section II.
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9.
  • Naqvi, Salman Raza, et al. (författare)
  • Pyrolysis of high-ash sewage sludge : Thermo-kinetic study using TGA and artificial neural networks
  • 2018
  • Ingår i: Fuel. - Oxon, UK : Elsevier Ltd. - 0016-2361 .- 1873-7153. ; 233, s. 529-538
  • Tidskriftsartikel (refereegranskat)abstract
    • Pyrolysis of high-ash sewage sludge (HASS) is a considered as an effective method and a promising way for energy production from solid waste of wastewater treatment facilities. The main purpose of this work is to build knowledge on pyrolysis mechanisms, kinetics, thermos-gravimetric analysis of high-ash (44.6%) sewage sludge using model-free methods & results validation with artificial neural network (ANN). TG-DTG curves at 5,10 and 20 °C/min showed the pyrolysis zone was divided into three zone. In kinetics, E values of models ranges are; Friedman (10.6–306.2 kJ/mol), FWO (45.6–231.7 kJ/mol), KAS (41.4–232.1 kJ/mol) and Popescu (44.1–241.1 kJ/mol) respectively. ΔH and ΔG values predicted by OFW, KAS and Popescu method are in good agreement and ranged from (41–236 kJ/mol) and 53–304 kJ/mol, respectively. Negative value of ΔS showed the non-spontaneity of the process. An artificial neural network (ANN) model of 2 * 5 * 1 architecture was employed to predict the thermal decomposition of high-ash sewage sludge, showed a good agreement between the experimental values and predicted values (R2 ⩾ 0.999) are much closer to 1. Overall, the study reflected the significance of ANN model that could be used as an effective fit model to the thermogravimetric experimental data. © 2018 Elsevier Ltd
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  • Resultat 1-9 av 9

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