| 1. |
- Abid, Muhammad Adil, et al.
(författare)
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A Genetic Algorithm for Optimizing Mobile Stroke Unit Deployment
- 2023
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Ingår i: Procedia Computer Science. - : Elsevier. - 1877-0509. ; 225, s. 3536-3545
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Tidskriftsartikel (refereegranskat)abstract
- A mobile stroke unit (MSU) is an advanced ambulance equipped with specialized technology and trained healthcare personnel to provide on-site diagnosis and treatment for stroke patients. Providing efficient access to healthcare (in a viable way) requires optimizing the placement of MSUs. In this study, we propose a time-efficient method based on a genetic algorithm (GA) to find the most suitable ambulance sites for the placement of MSUs (given the number of MSUs and a set of potential sites). We designed an efficient encoding scheme for the input data (the number of MSUs and potential sites) and developed custom selection, crossover, and mutation operators that are tailored according to the characteristics of the MSU allocation problem. We present a case study on the Southern Healthcare Region in Sweden to demonstrate the generality and robustness of our proposed GA method. Particularly, we demonstrate our method's flexibility and adaptability through a series of experiments across multiple settings. For the considered scenario, our proposed method outperforms the exhaustive search method by finding the best locations within 0.16, 1.44, and 10.09 minutes in the deployment of three MSUs, four MSUs, and five MSUs, resulting in 8.75x, 16.36x, and 24.77x faster performance, respectively. Furthermore, we validate the method's robustness by iterating GA multiple times and reporting its average fitness score (performance convergence). In addition, we show the effectiveness of our method by evaluating key hyperparameters, that is, population size, mutation rate, and the number of generations.
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| 2. |
- Alkhabbas, Fahed, et al.
(författare)
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A Commitment-Based Approach to Realize Emergent Configurations in the Internet of Things
- 2017
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Ingår i: Software Architecture Workshops (ICSAW), 2017 IEEE International Conference on. - : IEEE. ; , s. 88-91
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Konferensbidrag (refereegranskat)abstract
- The Internet of Things (IoT) involves intelligent, heterogeneous, autonomous and often distributed things which interact and collaborate to achieve common goals. A useful concept for supporting this effort is Emergent Configuration (EC), which consists of a dynamic set of things, with their functionalities and services, that cooperate temporarily to achieve a goal. In this paper we introduce a commitment-based approach that exploits the concept of commitments to realize ECs. More specifically, (i) we present a conceptual model for commitment-based ECs, (ii) we use the smart meeting room scenario to illustrate how ECs are realized via commitments.
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| 3. |
- Amouzad Mahdiraji, Saeid, et al.
(författare)
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A Framework for Constructing Discrete Event Simulation Models for Emergency Medical Service Policy Analysis
- 2022
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Ingår i: Procedia Computer Science. - : Elsevier BV. - 1877-0509. ; 210, s. 133-140
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Konferensbidrag (refereegranskat)abstract
- Constructing simulation models can be a complex and time-consuming task, in particular if the models are constructed from scratch or if a general-purpose simulation modeling tool is used. In this paper, we propose a model construction framework, which aims to simplify the process of constructing discrete event simulation models for emergency medical service (EMS) policy analysis. The main building blocks used in the framework are a set of general activities that can be used to represent different EMS care chains modeled as flowcharts. The framework allows to build models only by specifying input data, including demographic and statistical data, and providing a care chain of activities and decisions. In a case study, we evaluated the framework by using it to construct a model for the simulation of the EMS activities related to acute stroke. Our evaluation shows that the predefined activities included in the framework are sufficient to build a simulation model for the rather complex case of acute stroke.
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| 4. |
- Amouzad Mahdiraji, Saeid, et al.
(författare)
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A Micro-Level Simulation Model for Analyzing the Use of MSUs in Southern Sweden
- 2021
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Ingår i: Procedia Computer Science : 12th International Conference on Emerging Ubiquitous Systems and Pervasive Networks, EUSPN 2021 / 11th International Conference on Current and Future Trends of Information and Communication Technologies in Healthcare, ICTH 2021 - 12th International Conference on Emerging Ubiquitous Systems and Pervasive Networks, EUSPN 2021 / 11th International Conference on Current and Future Trends of Information and Communication Technologies in Healthcare, ICTH 2021. - : Elsevier BV. ; 198, s. 132-139
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Konferensbidrag (refereegranskat)abstract
- A mobile stroke unit (MSU) is a special type of ambulance, where stroke patients can be diagnosed and provided intravenous treatment, hence allowing to cut down the time to treatment for stroke patients. We present a discrete event simulation (DES) model to study the potential benefits of using MSUs in the southern health care region of Sweden (SHR). We included the activities and actions used in the SHR for stroke patient transportation as events in the DES model, and we generated a synthetic set of stroke patients as input for the simulation model. In a scenario study, we compared two scenarios, including three MSUs each, with the current situation, having only regular ambulances. We also performed a sensitivity analysis to further evaluate the presented DES model. For both MSU scenarios, our simulation results indicate that the average time to treatment is expected to decrease for the whole region and for each municipality of SHR. For example, the average time to treatment in the SHR is reduced from 1.31h in the baseline scenario to 1.20h and 1.23h for the two MSU scenarios. In addition, the share of stroke patients who are expected to receive treatment within one hour is increased by a factor of about 3 for both MSU scenarios.
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| 5. |
- Amouzad Mahdiraji, Saeid, et al.
(författare)
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An Optimization Model for the Placement of Mobile Stroke Units
- 2024
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Ingår i: Advanced Research in Technologies, Information, Innovation and Sustainability - 3rd International Conference, ARTIIS 2023, Proceedings. - : Springer. - 1865-0937 .- 1865-0929. - 9783031488573 - 9783031488580 ; 1935 CCIS, s. 297-310
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Konferensbidrag (refereegranskat)abstract
- Mobile Stroke Units (MSUs) are specialized ambulances that can diagnose and treat stroke patients; hence, reducing the time to treatment for stroke patients. Optimal placement of MSUs in a geographic region enables to maximize access to treatment for stroke patients. We contribute a mathematical model to optimally place MSUs in a geographic region. The objective function of the model takes the tradeoff perspective, balancing between the efficiency and equity perspectives for the MSU placement. Solving the optimization problem enables to optimize the placement of MSUs for the chosen tradeoff between the efficiency and equity perspectives. We applied the model to the Blekinge and Kronoberg counties of Sweden to illustrate the applicability of our model. The experimental findings show both the correctness of the suggested model and the benefits of placing MSUs in the considered regions.
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| 6. |
- Amouzad Mahdiraji, Saeid
(författare)
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On the Use of Simulation and Optimization for the Analysis and Planning of Prehospital Stroke Care
- 2022
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Immediate treatment is of extreme importance for stroke patients. However, providing fast enough treatment for stroke patients is far from trivial, mainly due to logistical challenges and difficulties in diagnosing the correct stroke type. One way to reduce the time to treatment is to use so-called Mobile Stroke Units (MSUs), which allows to diagnose and provide treatment for stroke patients already at the patient scene. A well-designed stroke transport policy is vital to improve the access to treatment for stroke patients. Simulation and mathematical optimization are useful approaches for assessing and optimizing stroke transport policies, without endangering the health of the patients.The main purpose of this thesis is to contribute to improving the situation for stroke patients and to reducing the social impacts of stroke. The aim is to study how to use simulation and optimization to achieve improved analysis and planning of prehospital stroke care. In particular, we focus on assessing the potential use of MSUs in a geographic area. In this thesis, optimization is used to identify the optimal locations of MSUs, and simulation is used to assess different stroke transport policies, including MSU locations. The results of this thesis aim to support public health authorities when making decisions in the prehospital stroke care domain.In order to fulfill the aim of this thesis, we develop and analyze a number of different simulation and optimization models. First, we propose a macro-level simulation model, an average time to treatment estimation model, used to estimate the expected time to treatment for different parts of a geographic region. Using the proposed model, we generate two different MSU scenarios to explore the potential benefits of employing MSUs in Sweden’s southern healthcare region (SHR). Second, we present an optimization model to identify the best placement of MSUs while making a trade-off between the efficiency and equity perspectives, providing maximum population coverage and equal service for all patients, respectively. The trade-off function used in the model makes use of the concepts of weighted average time to treatment to model efficiency and the time difference between the expected time to treatment for different geographical areas to model equity. In a scenario study applied in the SHR, we evaluate our optimization model by comparing the current situation with three MSU scenarios, including 1, 2, and 3 MSUs.Third, we present a micro-level discrete event simulation model to assess stroke transport policies, including MSUs, allowing us to model the behaviors of individual entities, such as patients and emergency vehicles, over time. We generate a synthetic set of stroke patients using a Poisson distribution, used as input in a scenario study.Finally, we present a modeling framework with reusable components, which aims to facilitate the construction of discrete event simulation models in the emergency medical services domain. The framework consists of a number of generic activities, which can be used to represent healthcare chains modeled in the form of flowcharts. As the framework includes activities and policies modeled on the general level, the framework can be used to create models only by providing input data and a care chain specification. We evaluate the framework by using it to build a model for simulating EMS activities related to the complex case of acute stroke.
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| 7. |
- Amouzad Mahdiraji, Saeid, et al.
(författare)
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Simulation-based Analysis of Co-dispatching in Prehospital Stroke Care
- 2024
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Ingår i: Procedia Computer Science. - 1877-0509. ; 238, s. 412-419
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Tidskriftsartikel (refereegranskat)abstract
- A mobile stroke unit (MSU) is a specialized ambulance, enabling to shorten the time to diagnosis and treatment for stroke patients. In the current paper, we present a simulation-based approach to study the potential impacts of collaborative use of regular ambulances and MSUs in prehospital transportation for stroke patients, denoted as co-dispatching. We integrated a co-dispatch policy in an existing modeling framework for constructing emergency medical services simulation models. In a case study, we applied the extended framework to southern Sweden to evaluate the effectiveness of using the co-dispatch policy for different types of stroke. The results indicate reduced time to diagnosis and treatment for stroke patients when using the co-dispatch policy compared to the situation where either a regular ambulance or an MSU is assigned for a stroke incident.
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| 8. |
- Casserfelt, Karl, et al.
(författare)
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An investigation of transfer learning for deep architectures in group activity recognition
- 2019
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Ingår i: 2019 IEEE International Conference On Pervasive Computing and Communications Workshops (Percom Workshops). - : IEEE. ; , s. 58-64
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Konferensbidrag (refereegranskat)abstract
- Pervasive technologies permeating our immediate surroundings provide a wide variety of means for sensing and actuating in our environment, having a great potential to impact the way we live, but also how we work. In this paper, we address the problem of activity recognition in office environments, as a means for inferring contextual information in order to automatically and proactively assists people in their daily activities. To this end we employ state-of-the-art image processing techniques and evaluate their capabilities in a real-world setup. Traditional machine learning is characterized by instances where both the training and test data share the same distribution. When this is not the case, the performance of the learned model is deteriorated. However, often times, the data is expensive or difficult to collect and label. It is therefore important to develop techniques that are able to make the best possible use of existing data sets from related domains, relative to the target domain. To this end, we further investigate in this work transfer learning techniques in deep learning architectures for the task of activity recognition in office settings. We provide herein a solution model that attains a 94% accuracy under the right conditions.
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| 9. |
- Ekedahl, Ulrik, et al.
(författare)
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Lessons Learned from Adapting "Things" to IoT Platforms in Research and Teaching
- 2018
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Ingår i: SAC '18. - New York, NY, USA : ACM Digital Library. - 9781450351911 ; , s. 1457-1460
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Konferensbidrag (refereegranskat)abstract
- This study presents lessons learned based on practical experiences of connecting devices to internet-of-things platforms in the context of research and academic coursework. The experiences are gathered from six research projects, one undergraduate course, and a few undergraduate theses over a three-year period. The lessons learned include: the trade-off of rapid prototyping over security is very common, example source code is not up to production standards, adherence to standards speeds development, debugging support for IoT systems is lacking, open source licenses varies, poor platform interoperability, and the array of service fees among platform providers obstruct cost comparisons.
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| 10. |
- Florea, George Albert, 1990-, et al.
(författare)
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Multimodal Deep Learning for Group Activity Recognition in Smart Office Environments
- 2020
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Ingår i: Future Internet. - : MDPI. - 1999-5903. ; 12:8
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Tidskriftsartikel (refereegranskat)abstract
- Deep learning (DL) models have emerged in recent years as the state-of-the-art technique across numerous machine learning application domains. In particular, image processing-related tasks have seen a significant improvement in terms of performance due to increased availability of large datasets and extensive growth of computing power. In this paper we investigate the problem of group activity recognition in office environments using a multimodal deep learning approach, by fusing audio and visual data from video. Group activity recognition is a complex classification task, given that it extends beyond identifying the activities of individuals, by focusing on the combinations of activities and the interactions between them. The proposed fusion network was trained based on the audio-visual stream from the AMI Corpus dataset. The procedure consists of two steps. First, we extract a joint audio-visual feature representation for activity recognition, and second, we account for the temporal dependencies in the video in order to complete the classification task. We provide a comprehensive set of experimental results showing that our proposed multimodal deep network architecture outperforms previous approaches, which have been designed for unimodal analysis, on the aforementioned AMI dataset.
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