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| 2. |
- T., Lennvall, et al.
(författare)
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Handling aperiodic tasks in diverse real-time systems via plug-ins
- 2002
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Ingår i: Proceedings - 5th IEEE International Symposium on Object-Oriented Real-Time Distributed Computing, ISORC 2002. - 0769515584 - 9780769515588 ; , s. 137-144
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Konferensbidrag (refereegranskat)abstract
- Functionality for various services of scheduling algorithms is typically provided as extensions to a basic algorithm. A similar approach dominates operating system functionality: implementation of the actual real-time scheduling algorithm. In this paper, we propose the use of a plug-in approach to add functionality to existing scheduling schemes and provide for easy, replacement on the operating system level. In particular, we present an architecture to disentangle actual real-time scheduling from dispatching and other kernel routines with a small API, suited for a variety of scheduling schemes as plug-ins. We detail two plug-ins for aperiodic task handling and how they can extend two target systems, table-driven and earliest deadline first scheduling, using the approach presented.
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| 3. |
- Kullingsjö, Lars-Henrik, 1984, et al.
(författare)
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Conflicting interests in defining an 'optimal' battery size when introducing the PHEV?
- 2014
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Ingår i: 27th World Electric Vehicle Symposium and Exhibition, EVS 2014; Barcelona; Spain; 17 November 2013 through 20 November 2013. ; , s. Art. no. 6915025-
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Konferensbidrag (refereegranskat)abstract
- The PHEV is an interesting option for reducing greenhouse gas emissions from transport or to increase energy security without losing performance in car operation. However finding an optimal battery size is of great importance for the overall economic and environmental performance of the PHEVs. This study investigates the resulting vehicle design, and fleet composition and performance when optimising the PHEV battery with respect to different objective functions possibly reflecting different actors’ interest: number of PHEVs, cumulative cost savings and share of electric driving respectively under various assumptions concerning policies and costs. A recently available data set of car movements, containing 445 privately driven Swedish cars that have been measured with GPS-equipment for 1-2 months each is utilized to get a representative car fleet. We find that the battery size and fleet performance are heavily influenced by not only the choice of objective function for the optimization but also by its interaction with the cost structure and performance requirement in the transition from an energy efficient fuel-driven car to a PHEV. The effect of different policies may also vary depending on these conditions and may favour various actors’ interests differently. We conclude that these aspects are important to consider both when designing vehicles and when formulating policies for the introduction of PHEVs.
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| 4. |
- Okin, Peter M., et al.
(författare)
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Digoxin use and risk of mortality in hypertensive patients with atrial fibrillation
- 2015
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Ingår i: Journal of Hypertension. - 0263-6352 .- 1473-5598. ; 33:7, s. 1480-1486
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Tidskriftsartikel (refereegranskat)abstract
- Background: Digoxin is widely used for rate control of atrial fibrillation. However, recent studies have reported conflicting results on the association of digoxin with mortality when used in patients with atrial fibrillation. Moreover, the relationship of digoxin use to mortality in hypertensive patients with atrial fibrillation has not been examined.Methods and results: All-cause mortality was examined in relation to in-treatment digoxin use in 937 hypertensive patients with ECG left ventricular hypertrophy in atrial fibrillation at baseline (n = 134) or who developed atrial fibrillation during follow-up (n = 803), randomly assigned to losartan or atenolol-based treatment, in post-hoc analysis of a substudy of the Losartan Intervention For Endpoint Reduction in hypertension (LIFE) trial. During 4.7 ± 1.1 years of mean follow-up, 167 patients died (17.8%) and 372 (39.7%) were treated with digoxin. In univariate Cox analyses, in-treatment digoxin use, entered as a time-varying covariate, was associated with a 61% higher risk of dying (hazard ratio 1.61, 95% confidence interval 1.18–2.19, P = 0.003). After adjusting for other univariate predictors of death in this population, including age, diabetes, history of ischemic heart disease, stroke, or heart failure, baseline Cornell product, QRS duration, heart rate, serum glucose, creatinine and high-density lipoprotein cholesterol, and a propensity score for digoxin use entered as standard covariates, and for in-treatment heart rate, pulse pressure, and Sokolow–Lyon voltage treated as time-varying covariates, digoxin use was no longer a significant predictor of mortality (hazard ratio 1.04, 95% confidence interval 0.73–1.48, P = 0.839).Conclusion: In hypertensive patients with ECG left ventricular hypertrophy with existing or new atrial fibrillation, digoxin use is not associated with a significantly increased risk of all-cause mortality after adjusting for other independent predictors of death and for the factors associated with the propensity to use digoxin in this population. These findings suggest that factors other than digoxin use may account for the increased mortality found with digoxin use in some studies.
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| 5. |
- Pajevic, Ljubica, et al.
(författare)
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Modeling opportunistic communication with churn
- 2016
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Ingår i: Computer Communications. - : Elsevier. - 0140-3664 .- 1873-703X.
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Tidskriftsartikel (refereegranskat)abstract
- In opportunistic networking, characterizing contact patterns between mobile users is essential for assessing feasibility and performance of opportunistic applications. There has been significant efforts in deriving this characterization, based on observations and trace analyses; however, most of the previously established results were obtained by studying contact opportunities at large spatial and temporal scales. Moreover, the user population is considered to be constant: no user can join or leave the system. Yet, there are many examples of scenarios which do not fully adhere to the previous assumption and cannot be accurately described at large scales. Urban environments, such as smaller city districts, are characterized by highly dynamic user populations. We believe that scenarios with varying population require further investigation. In this paper, we present a novel modeling approach to study operation of opportunistic applications in scenarios where the population size is subjected to frequent changes, that is, it exhibits churn. We examine two location-based content sharing schemes: a purely opportunistic case and an infrastructure-supported content sharing scheme, for which we provide stochastic models based on stochastic differential equations (SDEs). We validate our models in five scenarios: a city area, subway station, conference, campus, and a scenario with a synthetic mobility model and we show that the models provide good representations of the investigated scenarios.
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| 6. |
- Raidla, Annelie, et al.
(författare)
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Outcomes of Establishing an Urgent Care Centre in the Same Location as an Emergency Department
- 2020
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Ingår i: Sustainability. - : MPDI. - 2071-1050. ; 12:19
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Tidskriftsartikel (refereegranskat)abstract
- The emergency department (ED) is one of the busiest facilities in a hospital, and it is frequently described as a bottleneck that limits space and structures, jeopardising surge capacity during Major Incidents and Disasters (MIDs) and pandemics such as the COVID 19 outbreak. One remedy to facilitate surge capacity is to establish an Urgent Care Centre (UCC), i.e., a secondary ED, co-located and in close collaboration with an ED. This study investigates the outcome of treatment in an ED versus a UCC in terms of length of stay (LOS), time to physician (TTP) and use of medical services. If it was possible to make these parameters equal to or even less than the ED, UCCs could be used as supplementary units to the ED, improving sustainability. The results show reduced waiting times at the UCC, both in terms of TTP and LOS. In conclusion, creating a primary care-like facility in close proximity to the hospitals may not only relieve overcrowding of the hospital's ED in peacetime, but it may also provide an opportunity for use during MIDs and pandemics to facilitate the victims of the incident and society as a whole.
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| 7. |
- Raihan, Shafkat, et al.
(författare)
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A Belief Rule Base Approach to Support Comparison of Digital Speech Signal Features for Parkinson’s Disease Diagnosis
- 2021
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Ingår i: Brain Informatics. - Cham : Springer. ; , s. 388-400
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Konferensbidrag (refereegranskat)abstract
- Parkinson’s disease is a neurological disorder. It affects the structures of the central and peripheral nervous system that control movement. One of the symptoms of Parkinson’s disease is difficulty in speaking. Hence, analysis of speech signal of patients may provide valuable features for diagnosing. Previous works on diagnosis based on speech data have employed machine learning and deep learning techniques. However, these approaches do not address the various uncertainties in data. Belief rule based expert system (BRBES) is an approach that can reason under various forms of data uncertainty. Thus, the main objective of this research is to compare the potential of BRBES on various speech signal features of patients of parkinson’s disease. The research took into account various types of standard speech signal features such MFCCs, TQWTs etc. A BRBES was trained on a dataset of 188 patients of parkinson’s disease and 64 healthy candidates with 5-fold cross validation. It was optimized using an exploitive version of the nature inspired optimization algorithm called BRB-based adaptive differential evolution (BRBaDE). The optimized model performed better than explorative BRBaDE, genetic algorithm and MATLAB’s FMINCON optimization on most of these features. It was also found that for speech based diagnosis of Parkinson’s disease under uncertainty, the features such as Glottis Quotient, Jitter variants, MFCCs, RPDE, DFA and PPE are relatively more suitable.
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| 8. |
- Raihan, S. M. Shafkat, et al.
(författare)
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A Belief Rule Based Expert System to Diagnose Alzheimer’s Disease Using Whole Blood Gene Expression Data
- 2022
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Ingår i: Brain Informatics: 15th International Conference, BI 2022, Padua, Italy, July 15–17, 2022, Proceedings. - Cham : Springer. - 9783031150364 - 9783031150371 ; , s. 301-315
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Konferensbidrag (refereegranskat)abstract
- Alzheimer’s disease (AD) is a degenerative neurological disease that is the most common cause of dementia. It is also the fifth-greatest reason for death in adults aged 65 and over. However, there is no accurate way of diagnosing neurological Alzheimer’s disorders in medical research. Blood gene expression analysis offers a realistic option for identifying those at risk of AD. Blood gene expression patterns have previously proved beneficial in diagnosing several brain disorders, despite the blood-brain barrier’s restricted permeability. The most extensively used statistical machine learning and deep learning algorithms are data-driven and do not address data uncertainty. Belief Rule-Based Expert System (BRBES) is an approach that can identify various forms of uncertainty in data and reason using evidential reasoning. No previous research studies have examined BRBES’ performance in diagnosing AD. As a result, this study aims to identify how effective BRBES is at diagnosing Alzheimer’s disease from blood gene expression data. We used a gradient-free technique to optimize the BRBES because prior research had shown the limits of gradient-based optimization. We have also attempted to address the class imbalance problem using BRBES’ consequent utility parameters. Finally, after 5-fold cross-validation, we compared our model to three classic ML models, finding that our model had a greater specificity than the other three models across all folds. The average specificity of our models for all folds was 32%
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| 9. |
- Raihan Uddin, M., et al.
(författare)
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Energy analysis of a solar driven vaccine refrigerator using environment-friendly refrigerants for off-grid locations
- 2021
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Ingår i: Energy Conversion and Management. - : Elsevier Ltd. - 2590-1745. ; 11
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Tidskriftsartikel (refereegranskat)abstract
- In many remote localities, one of the underlying reasons for not receiving life-saving vaccines is the lack of electricity to store the vaccines in the required refrigerated conditions. Solar Photovoltaic (PV) refrigerators have been considered as a viable and green solution to store the vaccines in remote localities having no access to electricity. In this paper, a detailed methodology has been presented for the performance evaluation of a solar PV powered vaccine refrigerator for remote locations. Thermal modelling with hourly cooling load calculations and refrigeration cycle simulations were carried out. The performance parameters for three environment-friendly refrigerants: R152a, R1234yf, and R1234ze(E) has been compared against the commonly used R134a for two remote, off-grid locations in Bangladesh and South Sudan. The energy systems comprising of solar PV panels and batteries to run the refrigerator were modelled in HOMER software for techno-economic optimizations. For both the locations, R152a was found to be the best performing refrigerant exhibiting higher COP (2%−5.29%) as compared to the other refrigerants throughout the year, while R1234ze(E) exhibited COPs on par with R134a, and R1234yf had the least performance. Techno-economic analysis showed an energy system providing electricity to the refrigerator with R152a also had lower levelized cost of electricity (0.48%−2.54%) than the systems having other refrigerants in these locations.
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