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  • 301.
    Ahmed, Mobyen Uddin
    et al.
    Mälardalen University, School of Innovation, Design and Engineering.
    Begum, Shahina
    Mälardalen University, School of Innovation, Design and Engineering.
    Funk, Peter
    Mälardalen University, School of Innovation, Design and Engineering.
    An Overview of three Medical Applications Using Hybrid Case-Based Reasoning2012Conference paper (Refereed)
    Abstract [en]

    Today more and more patient journals are stored electronically but they are rarely used for more than statistical purpose. In this paper we present an approach where clinical patient journals are used for improved clinical decision making on an individual level. The underlying assumption is that medical staff benefit from comparing a specific patient with similar patient. By comparing symptoms, diagnosis, medication and outcome in an individual level they are able to make more informed decisions at the point of care. This paper presents some parts of our more than ten years research efforts in the area and some of the projects and their underlying hybrid approaches. As a foundation for all our projects we use case-based reasoning (CBR) research in combination with techniques from artificial intelligence, data mining, statistics and search techniques. Three systems are presented in two medical domains 1) decision support for stress diagnosis 2) decision support for stress treatment and 3) decision support for post-operative pain treatment and discuss results and lessons learned.

  • 302.
    Ahmed, Mobyen Uddin
    et al.
    Mälardalen University, School of Innovation, Design and Engineering.
    Begum, Shahina
    Mälardalen University, School of Innovation, Design and Engineering.
    Funk, Peter
    Mälardalen University, School of Innovation, Design and Engineering.
    Case studies on the clinical applications using case-based reasoning2012In: 2012 Federated Conference on Computer Science and Information Systems, FedCSIS 2012, 2012, p. 3-10Conference paper (Refereed)
    Abstract [en]

    Case-Based Reasoning (CBR) is a promising Artificial Intelligence (AI) method that is applied for problem solving tasks. This approach is widely used in order to develop Clinical Decision Support System (CDSS). A CDSS for diagnosis and treatment often plays a vital role and brings essential benefits for clinicians. Such a CDSS could function as an expert for a less experienced clinician or as a second option/opinion of an experienced clinician to their decision making task. This paper presents the case studies on 3 clinical Decision Support Systems as an overview of CBR research and development. Two medical domains are used here for the case studies: case-study-1) CDSS for stress diagnosis case-study-2) CDSS for stress treatment and case-study-3) CDSS for postoperative pain treatment. The observation shows the current developments, future directions and pros and cons of the CBR approach. Moreover, the paper shares the experiences of developing 3CDSS in medical domain in terms of case study.

  • 303.
    Ahmed, Mobyen Uddin
    et al.
    Mälardalen University, School of Innovation, Design and Engineering.
    Begum, Shahina
    Mälardalen University, School of Innovation, Design and Engineering.
    Funk, Peter
    Mälardalen University, School of Innovation, Design and Engineering.
    System Overview on a Clinical Decision Support System for Stress Management2012In: Proceedings of the ICCBR 2012 Workshops, 2012, p. 111-116Conference paper (Refereed)
    Abstract [en]

    There is an increased need for Clinical Decision Support Systems (CDSS) in the medical community as ICT technology is increasingly used in hospitals as more and more patient data is stored in computers. A CDSS has the potential to play a vital role and bring essential information and knowledge to the clinicians and function as a second opinion in their decision-making tasks. In this paper, a CDSS in stress management is presented where the CDSS can help the clinicians in order to diagnosis and treat stress related disorders. As a foundation for the CDSS, the Case-Based Reasoning (CBR) approach has been used as a core method of the system. The systems also combine other techniques from artificial intelligence in a multimodal manner, such as fuzzy logic, rule-based reasoning and textual information retrieval. In this paper we review our experiences and research efforts while developing the CDSS. The performance of the CDSS shows that the system can be useful both for trainee clinicians as an expert and as well as for senior clinicians as a second option. Moreover, the observation shows the current developments, and pros and cons of the CBR approach.

  • 304.
    Ahmed, Mobyen Uddin
    et al.
    Mälardalen University, School of Innovation, Design and Engineering.
    Begum, Shahina
    Mälardalen University, School of Innovation, Design and Engineering.
    Funk, Peter
    Mälardalen University, School of Innovation, Design and Engineering.
    The 3 CDSSs: An Overview and Application in Case-Based Reasoning2012In: The 27th annual workshop of the Swedish Artificial Intelligence Society (SAIS), Linköping: Linköping University Electronic Press, 2012, p. 25-32Conference paper (Refereed)
    Abstract [en]

    A computer-aided Clinical Decision SupportSystem (CDSS) for diagnosis and treatment often plays a vital role and brings essential benefits for clinicians. Such a CDSScould function as an expert for a less experienced clinician oras a second option/opinion of an experienced clinician to their decision making task. This paper presents 3 clinical DecisionSupport Systems as an overview of case-based reasoning (CBR) research and development. Two medical domains are used here for the case study 1) CDSS for stress diagnosis 2) CDSS for stress treatment and 3) CDSS for post-operative pain treatment.The observation shows the current developments, future direction and pros and cons of the CBR approach. Moreover,the paper shares the experiences of developing 3CDSS in medical domain.

  • 305.
    Ahmed, Mobyen Uddin
    et al.
    Mälardalen University, School of Innovation, Design and Engineering.
    Begum, Shahina
    Mälardalen University, School of Innovation, Design and Engineering.
    Funk, Peter
    Mälardalen University, School of Innovation, Design and Engineering.
    Xiong, Ning
    Mälardalen University, School of Innovation, Design and Engineering.
    FUZZY RULE-BASED CLASSIFICATION TO BUILD INITIAL CASE LIBRARY FOR CASE-BASED STRESS DIAGNOSIS2009In: Proceedings of the IASTED International Conference on Artificial Intelligence and Applications, AIA 2009 / [ed] M.H. Hamza, 2009, p. 225-230Conference paper (Refereed)
    Abstract [en]

    Case-Based Reasoning (CBR) is receiving increasedinterest for applications in medical decision support.Clinicians appreciate the fact that the system reasons withfull medical cases, symptoms, diagnosis, actions takenand outcomes. Also for experts it is often appreciated toget a second opinion. In the initial phase of a CBR systemthere are often a limited number of cases available whichreduces the performance of the system. If past cases aremissing or very sparse in some areas the accuracy isreduced. This paper presents a fuzzy rule-basedclassification scheme which is introduced into the CBRsystem to initiate the case library, providing improvedperformance in the stress diagnosis task. Theexperimental results showed that the CBR system usingthe enhanced case library can correctly classify 83% ofthe cases, whereas previously the correctness of theclassification was 61%. Consequently the proposedsystem has an improved performance with 22% in termsof accuracy. In terms of the discrepancy in classificationcompared to the expert, the goodness-of-fit value of thetest results is on average 87%. Thus by employing thefuzzy rule-based classification, the new hybrid system cangenerate artificial cases to enhance the case library.Furthermore, it can classify new problem cases previouslynot classified by the system.

  • 306.
    Ahmed, Mobyen Uddin
    et al.
    Mälardalen University, School of Innovation, Design and Engineering.
    Begum, Shahina
    Mälardalen University, School of Innovation, Design and Engineering.
    Funk, Peter
    Mälardalen University, School of Innovation, Design and Engineering.
    Xiong, Ning
    Multi-Modal and Multi-Purpose Case-based Reasoning in the Health Sciences2009In: PROCEEDINGS OF THE 8TH WSEAS INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE, KNOWLEDGE ENGINEERING AND DATA BASES / [ed] Leon Trilling et al, Cambridge, UK: WSEAS press , 2009, p. 378-383Conference paper (Refereed)
    Abstract [en]

    Case-based reasoning systems for medical application are increasingly multi-purpose systems and also multi-modal, using a variety of different methods and techniques to meet the challenges from the medical domain. It this paper, some of the recent medical case-based reasoning systems are classified according to their functionality and development properties. It shows how a particular multi-purpose and multi-modal case-based reasoning system solved these challenges. For this a medical case-based reasoning system in the domain of psychophysiology is used. 

  • 307.
    Ahmed, Mobyen Uddin
    et al.
    Mälardalen University, School of Innovation, Design and Engineering.
    Begum, Shahina
    Mälardalen University, School of Innovation, Design and Engineering.
    Funk, Peter
    Mälardalen University, School of Innovation, Design and Engineering.
    Xiong, Ning
    Mälardalen University, School of Innovation, Design and Engineering.
    von Schéele, Bo
    Mälardalen University, School of Innovation, Design and Engineering.
    A Multi-Module Case Based Biofeedback System for Stress Treatment2011In: Artificial Intelligence in Medicine, ISSN 0933-3657, E-ISSN 1873-2860, Vol. 51, no 2, p. 107-115Article in journal (Refereed)
    Abstract [en]

    Biofeedback is today a recognized treatment method for a number of physical and psychological problems. Experienced clinicians often achieve good results in these areas and their success largely builds on many years of experience and often thousands of treated patients. Unfortunately many of the areas where biofeedback is used are very complex, e.g. diagnosis and treatment of stress. Less experienced clinicians may even have difficulties to initially classify the patient correctly. Often there are only a few experts available to assist less experienced clinicians. To reduce this problem we propose a computer assisted biofeedback system helping in classification, parameter setting and biofeedback training. By adopting a case based approach in a computer-based biofeedback system, decision support can be offered to less experienced clinicians and provide a second opinion to experts. We explore how such a system may be designed and validate the approach in the area of stress where the system assists in the classification, parameter setting and finally in the training. In a case study we show that the case based biofeedback system outperforms novice clinicians based on a case library of cases authorized by an expert.

  • 308.
    Ahmed, Mobyen Uddin
    et al.
    Mälardalen University, School of Innovation, Design and Engineering.
    Begum, Shahina
    Mälardalen University, School of Innovation, Design and Engineering.
    Funk, Peter
    Mälardalen University, School of Innovation, Design and Engineering.
    Xiong, Ning
    Mälardalen University, School of Innovation, Design and Engineering.
    von Schéele, Bo
    Mälardalen University, School of Innovation, Design and Engineering.
    A Three Phase Computer Assisted Biofeedback Training System Using Case-Based Reasoning2008In: Proc. 9th European Conference on Case-based Reasoning, 2008, p. 57-68Conference paper (Refereed)
    Abstract [en]

    Biofeedback is a method gaining increased interest and showing good results for a number of physical and psychological problems. Biofeedback training is mostly guided by an experienced clinician and the results largely rely on the clinician's competence. In this paper we propose a three phase computer assisted sensor-based biofeedback decision support system assisting less experienced clinicians, acting as second opinion for experienced clinicians. The three phase CBR framework is deployed to classify a patient, estimate initial parameters and to make recommendations for biofeedback training by retrieving and comparing with previous similar cases in terms of features extracted. The three phases work independently from each other. Moreover, fuzzy techniques are incorporated into our CBR system to better accommodate uncertainty in clinicians reasoning as well as decision analysis. All parts in the proposed framework have been implemented and primarily validated in a prototypical system. The initial result shows how the three phases functioned with CBR technique to assist biofeedback training. Eventually the system enables the clinicians to allow a patient to train himself/herself unsupervised.

  • 309.
    Ahmed, Mobyen Uddin
    et al.
    Mälardalen University, School of Innovation, Design and Engineering.
    Begum, Shahina
    Mälardalen University, School of Innovation, Design and Engineering.
    Funk, Peter
    Mälardalen University, School of Innovation, Design and Engineering.
    Xiong, Ning
    Mälardalen University, School of Innovation, Design and Engineering.
    von Schéele, Bo
    Mälardalen University, School of Innovation, Design and Engineering.
    Case-based Reasoning for Diagnosis of Stress using Enhanced Cosine and Fuzzy Similarity2008In: Case-based Reasoning for Diagnosis of Stress using Enhanced Cosine and Fuzzy Similarity, ISSN 1867-366X, Vol. 1, p. 3-19Article in journal (Refereed)
    Abstract [en]

    Intelligent analysis of heterogeneous data and information sources for efficient decision support presents an interesting yet challenging task in clinical envi-ronments. This is particularly the case in stress medicine where digital patient re-cords are becoming popular which contain not only lengthy time series measurements but also unstructured textual documents expressed in form of natural languages. This paper develops a hybrid case-based reasoning system for stress di-agnosis which is capable of coping with both numerical signals and textual data at the same time. The total case index consists of two sub-parts corresponding to signal and textual data respectively. For matching of cases on the signal aspect we present a fuzzy similarity matching metric to accommodate and tackle the imprecision and uncertainty in sensor measurements. Preliminary evaluations have revealed that this fuzzy matching algorithm leads to more accurate similarity estimates for improved case ranking and retrieval compared with traditional distance-based matching crite-ria. For evaluation of similarity on the textual dimension we propose an enhanced cosine matching function augmented with related domain knowledge. This is im-plemented by incorporating Wordnet and domain specific ontology into the textual case-based reasoning process for refining weights of terms according to available knowledge encoded therein. Such knowledge-based reasoning for matching of tex-tual cases has empirically shown its merit in improving both precision and recall of retrieved cases with our initial medical databases. Experts in the domain are very positive to our system and they deem that it will be a valuable tool to foster wide-spread experience reuse and transfer in the area of stress diagnosis and treatment.

  • 310.
    Ahmed, Mobyen Uddin
    et al.
    Mälardalen University, School of Innovation, Design and Engineering.
    Begum, Shahina
    Mälardalen University, School of Innovation, Design and Engineering.
    Funk, Peter
    Mälardalen University, School of Innovation, Design and Engineering.
    Xiong, Ning
    Mälardalen University, School of Innovation, Design and Engineering.
    von Schéele, Bo
    Mälardalen University, School of Innovation, Design and Engineering.
    Case-based Reasoning for Diagnosis of Stress using Enhanced Cosine and Fuzzy Similarity2008In: Transactions on Case-Based Reasoning on Multimedia Data, ISSN 1867-366X, Vol. 1, no 1, p. 3-19Article in journal (Refereed)
    Abstract [en]

    Intelligent analysis of heterogeneous data and information sources for efficient decision support presents an interesting yet challenging task in clinical environments. This is particularly the case in stress medicine where digital patient records are becoming popular which contain not only lengthy time series measurements but also unstructured textual documents expressed in form of natural languages. This paper develops a hybrid case-based reasoning system for stress diagnosis which is capable of coping with both numerical signals and textual data at the same time. The total case index consists of two sub-parts corresponding to signal and textual data respectively. For matching of cases on the signal aspect we present a fuzzy similarity matching metric to accommodate and tackle the imprecision and uncertainty in sensor measurements. Preliminary evaluations have revealed that this fuzzy matching algorithm leads to more accurate similarity estimates for improved case ranking and retrieval compared with traditional distance-based matching criteria. For evaluation of similarity on the textual dimension we propose an enhanced cosine matching function augmented with related domain knowledge. This is implemented by incorporating Wordnet and domain specific ontology into the textual case-based reasoning process for refining weights of terms according to available knowledge encoded therein. Such knowledge-based reasoning for matching of textual cases has empirically shown its merit in improving both precision and recall of retrieved cases with our initial medical databases. Experts in the domain are very positive to our system and they deem that it will be a valuable tool to foster widespread experience reuse and transfer in the area of stress diagnosis and treatment.

  • 311.
    Ahmed, Mobyen Uddin
    et al.
    Mälardalen University, School of Innovation, Design and Engineering.
    Begum, Shahina
    Mälardalen University, School of Innovation, Design and Engineering.
    Funk, Peter
    Mälardalen University, School of Innovation, Design and Engineering.
    Xiong, Ning
    Mälardalen University, School of Innovation, Design and Engineering.
    von Schéele, Bo
    Mälardalen University, School of Innovation, Design and Engineering.
    Lindén, Maria
    Mälardalen University, School of Innovation, Design and Engineering.
    Folke, Mia
    Mälardalen University, School of Innovation, Design and Engineering.
    Intelligent Stress Management System2009In: Medicinteknikdagarna 2009, 2009Conference paper (Refereed)
    Abstract [en]

    Today, in our daily life we are subjected to a wide range of pressures. When the pressures exceed the extent that we are able to deal with then stress is trigged. High level of stress may cause serious health problems i.e. it reduces awareness of bodily symptoms. So, people may first notice it weeks or months later meanwhile the stress could cause more serious effect in the body and health. A difficult issue in stress management is to use biomedical sensor signals in the diagnosis and treatment of stress. This paper presents a case-based system that assists a clinician in diagnosis and treatment of stress. The system uses a finger temperature sensor and the variation in the finger temperature is one of the key features in the system. Several artificial intelligence techniques such as textual information retrieval, rule-based reasoning (RBR), and fuzzy logic have been combined together with case-based reasoning to enable more reliable and efficient diagnosis and treatment of stress. The performance has been validated implementing a research prototype and close collaboration with experts.

  • 312.
    Ahmed, Mobyen Uddin
    et al.
    Mälardalen University, School of Innovation, Design and Engineering.
    Begum, Shahina
    Mälardalen University, School of Innovation, Design and Engineering.
    Islam, Mohd. Siblee
    Mälardalen University, School of Innovation, Design and Engineering.
    Heart Rate and Inter-beat Interval Computation to Diagnose Stress2010Report (Other academic)
    Abstract [en]

    Problem in diagnosing of stress is an important issue. The variations in beat-to-beat alteration in the heart rate (HR) can provide an identification of stress. HR can be determined from the Electrocardiogram (ECG) signal. However, accurate detection of HR and inter-beat interval (IBI) values from the ECG waveform is important. This report presents a way of measuring the ECG signal together with the ECG component analysis such as QRS peak detection and HR calculation to use it in a computer-based stress diagnosis system.

  • 313.
    Ahmed, Mobyen Uddin
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Begum, Shahina
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Kerstis, Birgitta
    Mälardalen University, School of Health, Care and Social Welfare, Health and Welfare.
    Petrovic, Nikola
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Sandborgh, Maria
    Mälardalen University, School of Health, Care and Social Welfare, Health and Welfare.
    Third Eye: An Intelligent Assisting Aid for Visual Impairment Elderly2016In: Medicinteknikdagarna 2016 MTF, 2016Conference paper (Refereed)
    Abstract [en]

    Background Visually impaired older persons need support in daily activities, e.g. moving around inside the house; making and eating food and taking medicine independently. A system that simulates the environment based on both dynamic and static objects, identify obstacles, navigates and translates sensory information in voice would be valuable to support their daily activities. Today several sensors and camera-based systems are popular as ambient-assisted living tools for older adults. However, intelligent assisting aid (IAA) to support older individuals with a recently acquired visual impairment is limited. The proposed system ‘Third Eye’ focuses on the advanced research and development of an IAA to support older individuals with a recently acquired visual impairment. The main goal in this system is to provide a usable, feasible and cost-effective solution for older persons to support their daily activities using intelligent sensor based system. Method The system consists of the following five phases to meet several central challenges in developing IAA in such domain. • User-perspective, focuses on user-driven technical development, investigating needs of potential users. The study will have a participatory design with focus group interviews of lead users. • Sensor-based system, focuses on the identification obstacles based on ultrasounds and/or radio frequencies embedded in white-cane or weaker. • Camera-based system, focuses on image based information translation into voice embedded in white-cane or weaker or glasses. • System of systems, focuses on integration of above systems where knowledge is engineered and suitable representations are learned and reasoning for decisions are made [9]. • Experimental, focuses on usability and feasibility of the IAA, with idiographic and group studies Results The initial results have shown the necessity of the proposed AAI systems for older individuals with a recently acquired visual impairment. However, more extension work e.g., process and analyze the information and synthesize it with existing literature for developing the system is ongoing.

  • 314.
    Ahmed, Mobyen Uddin
    et al.
    Mälardalen University, School of Innovation, Design and Engineering.
    Begum, Shahina
    Mälardalen University, School of Innovation, Design and Engineering.
    Olsson, Erik
    Mälardalen University, School of Innovation, Design and Engineering.
    Xiong, Ning
    Mälardalen University, School of Innovation, Design and Engineering.
    Funk, Peter
    Mälardalen University, School of Innovation, Design and Engineering.
    Case-Based Reasoning for Medical and Industrial Decision Support Systems2010In: Successful Case-based Reasoning Applications, Springer, 2010, p. 7-52Chapter in book (Other academic)
    Abstract [en]

    The amount of medical and industrial experience and knowledge is rapidly growing and it is almost impossible to be up to date with everything. The demand of decision support system (DSS) is especially important in domains where experience and knowledge grow rapidly. However, traditional approaches to DSS are not always easy to adapt to a flow of new experience and knowledge and may also show a limitation in areas with a weak domain theory. This chapter explores the functionalities of Case-Based Reasoning (CBR) to facilitate experience reuse both in clinical and in industrial decision making tasks. Examples from the field of stress medicine and condition monitoring in industrial robots are presented here to demonstrate that the same approach assists both for clinical applications as well as for decision support for engineers. In the both domains, DSS deals with sensor signal data and integrate other artificial intelligence techniques into the CBR system to enhance the performance in a number of different aspects. Textual information retrieval, Rule-based Reasoning (RBR), and fuzzy logic are combined together with CBR to offer decision support to clinicians for a more reliable and efficient management of stress. Agent technology and wavelet transformations are applied with CBR to diagnose audible faults on industrial robots and to package such a system. The performance of the CBR systems have been validated and have shown to be useful in solving such problems in both of these domains.

  • 315.
    Ahmed, Mobyen Uddin
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Begum, ShahinaMälardalen University, School of Innovation, Design and Engineering, Embedded Systems.Raad, WasimKing Fahd University of Petroleum and Minerals, Dhahran, Saudi Arabia.
    Internet of Things Technologies for HealthCare: Third International Conference, HealthyIoT 2016, Västerås, Sweden, October 18-19, 2016, Revised Selected Papers2016Conference proceedings (editor) (Other academic)
    Abstract [en]

    This book constitutes the proceedings of the Third International Conference on Internet of Things (IoT) Technologies for HealthCare, HealthyIoT 2016, held in Västerås, Sweden, October 18-19, 2016. The conference also included the First Workshop on Emerging eHealth through Internet of Things (EHIoT 2016). IoT as a set of existing and emerging technologies, notions and services provides many solutions to delivery of electronic healthcare, patient care, and medical data management. The 31 revised full papers presented along with 9 short papers were carefully reviewed and selected from 43 submissions in total. The papers cover topics such as healthcare support for the elderly, real-time monitoring systems, security, safety and communication, smart homes and smart caring environments, intelligent data processing and predictive algorithms in e-Health, emerging eHealth IoT applications, signal processing and analysis, and smartphones as a healthy thing.

  • 316.
    Ahmed, Mobyen Uddin
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Björkman, Mats
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Causevic, Aida
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Fotouhi, Hossein
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Lindén, Maria
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    An Overview on the Internet of Things for Health Monitoring Systems2015In: 2nd EAI International Conference on IoT Technologies for HealthCare HealthyIoT2015, 2015Conference paper (Refereed)
    Abstract [en]

    The aging population and the increasing healthcare cost in hospitals are spurring the advent of remote health monitoring systems. Advances in physiological sensing devices and the emergence of reliable low-power wireless network technologies have enabled the design of remote health monitoring systems. The next generation Internet, commonly referred to as Internet of Things (IoT), depicts a world populated by devices that are able to sense, process and react via the Internet. Thus, we envision health monitoring systems that support Internet connection and use this connectivity to enable better and more reliable services. This paper presents an overview on existing health monitoring systems, considering the IoT vision. We focus on recent trends and the development of health monitoring systems in terms of: (1) health parameters, (2) frameworks, (3) wireless communication, and (4) security issues. We also identify the main limitations, requirements and advantages within these systems.

  • 317.
    Ahmed, Mobyen Uddin
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Björkman, Mats
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Lindén, Maria
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    A Generic System-level Framework for Self-Serve Health Monitoring System through Internet of Things(IoT)2015In: Studies in Health Technology and Informatics, Volume 211: Proceedings of the 12th International Conference on Wearable Micro and Nano Technologies for Personalized Health, 2–4 June 2015, Västerås, Sweden, 2015, Vol. 211, p. 305-307Conference paper (Refereed)
    Abstract [en]

    Sensor data are traveling from sensors to a remote server, data is analysed remotely in a distributed manner, and health status of a user is presented in real-time. This paper presents a generic system-level framework for a self-served health monitoring system through the Internet of Things (IoT) to facilities an efficient sensor data management.

  • 318.
    Ahmed, Mobyen Uddin
    et al.
    Mälardalen University, School of Innovation, Design and Engineering. ES (Embedded Systems).
    Brickman, Staffan
    Dengg, Alexander
    Fasth, Niklas
    Mihajlovic, Marko
    Norman, Jacob
    A Machine Learning Approach to Classify Pedestrians’ Event based on IMU and GPSIn: International Conference on Modern Intelligent Systems Concepts MISC'18Conference paper (Refereed)
    Abstract [en]

    This paper investigates and implements six Machine Learning (ML) algorithms, i.e. Artificial Neural Network (ANN), Support Vector Machine (SVM), Decision Tree (DT), Random Forest (RF), Extra Tree (ET), and Gradient Boosted Trees (GBT) to classify different Pedestrians’ events based on Inertial Measurement Unit (IMU) and Global Positioning System (GPS) signals. Pedestrians’ events are pedestrian movements as the first step of H2020 project called SimuSafe1 with a goal to reduce traffic fatalities by doing risk assessments of the pedestrians. The movements the MLs’ models are attempting to classify are standing, walking, and running. Data, i.e. IMU, GPS sensor signals and other contextual information are collected by a smartphone through a controlled procedure. The smartphone is placed in five different positions onto the body of participants, i.e. arm, chest, ear, hand and pocket. The recordings are filtered, trimmed, and labeled. Next, samples are generated from small overlapping sections from which time and frequency domain features are extracted. Three different experiments are conducted to evaluate the performances in term of accuracy of the MLs’ models in different circumstances. The best performing MLs’ models determined by the average accuracy across all experiments is Extra Tree (ET) with a classification accuracy of 91%. 

  • 319.
    Ahmed, Mobyen Uddin
    et al.
    Örebro University, Sweden.
    Espinosa, Jesica Rivero
    Technosite. Fundosa Group. R& D. Madrid, Spain.
    Reissner, Alenka
    Zveza Društev Upokojencev Slovenije Ljubljana, Slovenia.
    Domingo, Àlex
    Universitat Autònoma de Barcelona, Spain.
    Banaee, Hadi
    Örebro University, Sweden.
    Loutfi, Amy
    Örebro University, Sweden.
    Rafael-Palou, Xavier
    Barcelona Digital Technology Centre Spain.
    Self-Serve ICT-based Health Monitoring to Support Active Ageing2015In: 8th International Conference on Health Informatics HEALTHINF, 2015Conference paper (Refereed)
    Abstract [en]

    Today, the healthcare monitoring is not limited to take place in primary care facilities simply due to deployment of ICT. However, to support an ICT-based health monitoring, proper health parameters, sensor devices, data communications, approaches, methods and their combination are still open challenges. This paper presents a self-serve ICT-based health monitoring system to support active ageing by assisting seniors to participate in regular monitoring of elderly’s health condition. Here, the main objective is to facilitate a number of healthcare services to enable good health outcomes of healthy active living. Therefore, the proposed approach is identified and constructed three different kinds of healthcare services: 1) real time feedback generation service, 2) historical summary calculation service and 3) recommendation generation service. These services are implemented considering a number of health parameters, such as, 1) blood pressure, 2) blood glucose, 3) medication compliance, 4) weight monitoring, 5) physical activity, 6) pulse monitoring etc. The services are evaluated in Spain and Slovenia through 2 prototypical systems, i.e. year2prototype (Y2P) and year3prototype (Y3P) by 46 subjects (40 for Y2P and 6 for Y3P). The evaluation results show the necessity and competence of the proposed healthcare services. In addition, the prototypical system (i.e. Y3P) is found very much accepted and useful by most of the users.

  • 320.
    Ahmed, Mobyen Uddin
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Fotouhi, Hossein
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Köckemann, Uwe
    Örebro University, Sweden.
    Lindén, Maria
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Tomasic, Ivan
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Tsiftes, Nicolas
    RISE SICS, Stockholm, Sweden.
    Voigt, Thiemo
    RISE SICS, Stockholm, Sweden.
    Run-Time Assurance for the E-care@home System2018In: Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST, Volume 225, 2018, p. 107-110Conference paper (Refereed)
    Abstract [en]

    This paper presents the design and implementation of the software for a run-time assurance infrastructure in the E-care@home system. An experimental evaluation is conducted to verify that the run-time assurance infrastructure is functioning correctly, and to enable detecting performance degradation in experimental IoT network deployments within the context of E-care@home.

  • 321.
    Ahmed, Mobyen Uddin
    et al.
    Mälardalen University, School of Innovation, Design and Engineering.
    Funk, Peter
    Mälardalen University, School of Innovation, Design and Engineering.
    A Case-Based Retrieval System for Post-Operative Pain Treatment2011In: / [ed] Petra Perner and Georg Rub, Germany: IBaI , 2011, p. 30-41Conference paper (Refereed)
    Abstract [en]

    This paper presents a clinical decision support system based on case-basedretrieval approach to assist physicians in post-operative pain treatment. Here,the cases are formulated by combining regular features and features using anumerical visual analogue scale (NVAS) through a questionnaire. Featureabstraction is done both in problem and outcome description of a case in order toreduce the number of attributes. The system retrieves most similar cases with theiroutcomes. The outcome of each case brings benefits for physicians since it presentsboth severity and fast recovery by the applied treatment in post-operative patients.Therefore, we have introduced a two-layer case structure i.e., solution is the firstlayer and outcome is the second layer that better suits this medical application. Inthe system, the solution presents the treatment and the outcome contains recoveryinformation of a patient, something physicians are interested in, especially the riskof side effects and complications.

  • 322.
    Ahmed, Mobyen Uddin
    et al.
    Mälardalen University, School of Innovation, Design and Engineering.
    Funk, Peter
    Mälardalen University, School of Innovation, Design and Engineering.
    A Computer Aided System for Post-operative Pain Treatment Combining Knowledge Discovery and Case-Based Reasoning2012In: Lecture Notes in Computer Science, vol. 7466, Springer, 2012, p. 3-16Chapter in book (Refereed)
    Abstract [en]

    The quality improvement for individual postoperative-pain treatment is an important issue. This paper presents a computer aided system for physicians in their decision making tasks in post-operative pain treatment. Here, the system combines a Case-Based Reasoning (CBR) approach with knowledge discovery. Knowledge discovery is applied in terms of clustering in order to identify the unusual cases. We applied a two layered case structure for case solutions i.e. the treatment is in the first layer and outcome after treatment (i.e. recovery of the patient) is in the second layer. Moreover, a 2nd order retrieval approach is applied in the CBR retrieval step in order to retrieve the most similar cases. The system enables physicians to make more informed decisions since they are able to explore similar both regular and rare cases of post-operative patients. The two layered case structure is moving the focus from diagnosis to outcome i.e. the recovery of the patient, something a physician is especially interested in, including the risk of complications and side effects.

  • 323.
    Ahmed, Mobyen Uddin
    et al.
    Mälardalen University, School of Innovation, Design and Engineering.
    Funk, Peter
    Mälardalen University, School of Innovation, Design and Engineering.
    Mining Rare Cases in Post-Operative Pain by Means of Outlier Detection2011In: IEEE Symposium on Signal Processing and Information Technology (ISSPIT) 2011, IEEE , 2011, p. 35-41Conference paper (Refereed)
    Abstract [en]

    Rare cases are often interesting for health professionals, physicians, researchers and clinicians in order to reuse and disseminate experiences in healthcare. However, mining, i.e. identification of rare cases in electronic patient records, is non-trivial for information technology. This paper investigates a number of well-known clustering algorithms and finally applies a 2 nd order clustering approach by combining the Fuzzy C-means algorithm with the Hierarchical one. The approach was used to identify rare cases from 1572 patient cases in the domain of post-operative pain treatment. The results show that the approach enables the identification of rare cases in the domain of post-operative pain treatment and 18% of cases were identified as rare

  • 324.
    Ahmed, Mobyen Uddin
    et al.
    Mälardalen University, School of Innovation, Design and Engineering.
    Funk, Peter
    Mälardalen University, School of Innovation, Design and Engineering.
    Mining Rare Cases in Post-Operative Pain by Means of Outlier Detection2011Manuscript (preprint) (Other academic)
    Abstract [en]

    Rare cases are often interesting for healthprofessionals, physicians, researchers and clinicians in order toreuse and disseminate experiences in healthcare. However,mining, i.e. identification of rare cases in electronic patientrecords, is non-trivial for information technology. This paperinvestigates a number of well-known clustering algorithms andfinally applies a 2nd order clustering approach by combining theFuzzy C-means algorithm with the Hierarchical one. Theapproach is used in order to identify rare cases from 1572patient cases in the domain of post-operative pain management.The results show that the approach enables identification of rarecases in the domain of post-operative pain management and 18%of cases are identified as rare case.

  • 325.
    Ahmed, Mobyen Uddin
    et al.
    Örebro University, Sweden.
    Islam, Asif Moinul
    Örebro University, Sweden.
    Loutfi, Amy
    Örebro University, Sweden.
    A case-based patient identification system using pulse oximeter and a personalized health profile2012In: Proceedings of the ICCBR 2012 Workshops, Lyon, France, 2012, p. 117-128Conference paper (Refereed)
    Abstract [en]

    This paper proposes a case-based system framework in order to identify patient using their health parameters taken with physiological sensors. It combines a personalized health profiling protocol with a Case-Based Reasoning (CBR) approach. The personalized health profiling helps to determine a number of individual parameters which are important inputs for a clinician to make the final diagnosis and treatment plan. The proposed system uses a pulse oximeter that measures pulse rate and blood oxygen saturation. The measurements are taken through an android application in a smart phone which is connected with the pulseoximeter and bluetooth communication. The CBR approach helps clinicians to make a diagnosis, classification and treatment plan by retrieving the most similar previous case. The case may also be used to follow the treatment progress. Here, the cases are formulated with person’s contextual information and extracted features from sensor signal measurements. The features are extracted considering three domain analysis:1) time domain features using statistical measurement, 2) frequency domain features applying Fast Fourier Transform (FFT), and 3) time-frequency domain features applying Discrete Wavelet Transform (DWT). The initial result is acceptable that shows the advancement of the system while combining the personalized health profiling together with CBR.

  • 326.
    Ahmed, Mobyen Uddin
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Lindén, Maria
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Healthcare Service at Home: An Intelligent Health Monitoring System for Elderly2015In: Medicinteknikdagarna 2015 MFT 2015, 2015Conference paper (Refereed)
    Abstract [en]

    This paper presents an intelligent healthcare service to support active ageing by assisting seniors to participate in regular monitoring of elderly’s health condition. The proposed system is applicable to use in home environment and offers a self-service approach to monitor elderly’s health condition. According to the evaluation, the proposed system shows its necessity, competence and usefulness.

  • 327.
    Ahmed, Mobyen Uddin
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Lindén, Maria
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Multi-parameter Sensing Platform in ESS-H and E-care@home2017In: Joint conference of the European Medical and Biological Engineering Conference (EMBEC) and the Nordic-Baltic Conference on Biomedical Engineering and Medical Physics (NBC) EMBEC & NBC’17, 2017Conference paper (Refereed)
    Abstract [en]

    Considering the population of ageing, health monitoring of elderly at home have the possibility for a person to keep track on his/her health status, e.g. decreased mobility in a personal environment. This also shows the potential of real-time decision support, early detection of symptoms, following of health trends and context awareness [1]. The ongoing projects Embedded Sensor for Health (ESS-H)1 and E-care@home2 are focusing on health monitoring of elderly at home. This paper presents the implementation of multi-parameter sensing on an Android platform. The objectives are, both to follow health trends and to enabling real time monitoring.

  • 328.
    Ahmed, Mobyen Uddin
    et al.
    Örebro University, Sweden.
    Loutfi, Amy
    Örebro University, Sweden.
    Physical Activity Classification for Elderly Based on Pulse Rate2013In: Studies in Health Technology and Informatics, vol. 189, 2013, p. 152-157Conference paper (Refereed)
    Abstract [en]

    Physical activity is one of the key components for elderly in order to be actively ageing. However, it is difficult to differentiate and identify the body movement and actual physical activity using only accelerometer measurements. Therefore, this paper presents an application of a case-based retrieval classification scheme to classify the physical activity of elderly based on pulse rate measure- ments. Here, a case-based retrieval approach used the features extracted from both time and frequency domain. The evaluation result shows the best accuracy perfor- mance while considering the combination of time and frequency domain features. According to the evaluation result while considering the control measurements, the sensitivity, specificity and overall accuracy are achieved as 95%, 96% and 96%, respectively. Considering the test dataset, the system succeeded to identify 13 physical activities out of 16, i.e,. the percentage of the correctness was 81%.

  • 329.
    Ahmed, Mobyen Uddin
    et al.
    Örebro University, Sweden.
    Loutfi, Amy
    Örebro University, Sweden.
    Physical Activity Identification using Supervised Machine Learning and based on Pulse Rate2013In: International Journal of Advanced Computer Science and Applications IJACSA, ISSN 2156-5570, Vol. 4, no 7, p. 209-217Article in journal (Refereed)
    Abstract [en]

    Physical activity is one of the key components for elderly in order to be actively ageing. Pulse rate is a convenient physiological parameter to identify elderly’s physical activity since it increases with activity and decreases with rest. However, analysis and classification of pulse rate is often difficult due to personal variation during activity. This paper proposed a Case-Based Reasoning (CBR) approach to identify physical activity of elderly based on pulse rate. The proposed CBR approach has been compared with the two popular classification techniques, i.e. Support Vector Machine (SVM) and Neural Network (NN). The comparison has been conducted through an empirical experimental study where three experiments with 192 pulse rate measurement data are used. The experiment result shows that the proposed CBR approach outperforms the other two methods. Finally, the CBR approach identifies physical activity of elderly 84% accurately based on pulse rate.

  • 330.
    Ahmed, Mobyen Uddin
    et al.
    Mälardalen University, Department of Computer Science and Electronics.
    Olsson, Erik
    Mälardalen University, Department of Computer Science and Electronics.
    Funk, Peter
    Mälardalen University, Department of Computer Science and Electronics.
    Xiong, Ning
    Mälardalen University, Department of Computer Science and Electronics.
    A Case-Based Reasoning System for Knowledge and Experience Reuse2007In: Proceedings of the 24th annual workshop of the Swedish Artificial Intelligence Society, 2007, p. 70-80Conference paper (Refereed)
    Abstract [en]

    Experience is one of the most valuable assets technicians and engineer have and may have been collected during many years and both from successful solutions as well as from very costly mistakes. Unfortunately industry rarely uses a systematic approach for experience reuse. This may be caused by the lack of efficient tools facilitating experience distribution and reuse. We propose a case-based approach and tool to facilitate experience reuse more systematically in industry. It is important that such a tool allows the technicians to give the problem case in a flexible way to increase acceptance and use. The proposed tool enables more structured handling of experience and is flexible and can be adapted to different situations and problems. The user is able to input text in a structured way and possibly in combination with other numeric or symbolic features. The system is able to identify and retrieve relevant similar experiences for reuse.

  • 331.
    Ahmed, Mobyen Uddin
    et al.
    Mälardalen University, Department of Computer Science and Electronics.
    Olsson, Erik
    Mälardalen University, Department of Computer Science and Electronics.
    Funk, Peter
    Mälardalen University, Department of Computer Science and Electronics.
    Xiong, Ning
    Mälardalen University, Department of Computer Science and Electronics.
    Efficient Condition Monitoring and Diagnosis Using a Case-Based Experience Sharing System2007In: The 20th International Congress and Exhibition on Condition Monitoring and Diagnostics Engineering Management, COMADEM 2007, Faro, Portugal, 2007, p. 305-314Conference paper (Refereed)
    Abstract [en]

    Industry has to adjust quickly to changes in their surroundings, for example reducing staff during recession and increasing staff when the market demands it. These factors may cause rapid loss of experience, collected during many years, or require experienced staff to spend considerable resources in training new staff, instead of focusing on production. This is recognised as very costly for companies and organisations today and also reduces competitiveness and productivity. Condition Monitoring, diagnostics and selection of efficient preventive or corrective actions is a task that often requires a high degree of expertise. This expertise is often gained through sometimes very expensive mistakes and can take many years to acquire leading to a few skilled experts. When they are not available due to changes in staff or retirements the company often faces serious problems that may be very expensive, e.g. leading to a reduced productivity.

    If some deviation occurs in a machine, a fault report is often written; an engineer makes a diagnosis and may order spare parts to repair the machine. Fault report, spare parts, required time and statistics on performance after repair are often stored in different databases but so far not systematically reused. In this paper we present a Case-Based experience sharing system that enables reuse of experience in a more efficient way compared with what is mostly practiced in industry today. The system uses Case-Based-Reasoning (CBR) and limited Natural Language Processing. An important aspect of the experience management tool is that it is user-friendly and web-based to promote efficient experience sharing. The system should be able to handle both experiences that are only in house as well as sharing experience with other industries when there is no conflicting interest. Such a CBR based tool enables efficient experience gathering, management and reuse in production industries. The tool will facilitate the users with an interactive environment to communicate with each other for sharing their experiences. Depend on the user; the security level of the system will be varied to share knowledge among the collaborating companies.

    The system identifies the most relevant experiences to assess and resolve the current situation. The experience is stored and retrieved as a case in the collaborative space where experience from various companies may have been stored under many years. Reusing experience and avoiding expensive mistakes will increase the participating companies' competitiveness and also transfer valuable experience to their employees. One of the benefits is also the opportunity and facility to identify people with similar tasks and problems at different companies and enable them to share their experience, e.g. if a technician has solved a similar problem recently and is in the near, the most efficient solution may be to call the expert and ask for assistance. In future, one may access this tool through his/her mobile device via wireless or mobile communications using Global Positioning System, GPS, enables the system to suggest experts nearby, willing and able to share the knowledge and quickly assist in resolve the problem.

  • 332.
    Ahmed, Mobyen Uddin
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Rahman, Hamidur
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Begum, Shahina
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Quality index analysis on camera- A sed R-eak identification considering movements and light illumination2018In: Studies in Health Technology and Informatics, vol 249, IOS Press , 2018, p. 84-92Conference paper (Refereed)
    Abstract [en]

    This paper presents a quality index (QI) analysis on R-peak extracted by a camera system considering movements and light illumination. Here, the proposed camera system is compared with a reference system named Shimmer PPG sensor. The study considers five test subjects with a 15 minutes measurement protocol, where the protocol consists of several conditions. The conditions are: Normal sittings, head movements i.e., up/down/left/right/forward/backword, with light on/off and with moving flash on/off. A percentage of corrected R-peaks are calculated based on time difference in milliseconds (MS) between the R-peaks extracted both from camera-based and sensor-based systems. A comparison results between normal, movements, and lighting condition is presented as individual and group wise. Furthermore, the comparison is extended considering gender and origin of the subjects. According to the results, more than 90% R-peaks are correctly identified by the camera system with ±200 MS time differences, however, it decreases with while there is no light than when it is on. At the same time, the camera system shows more 95% accuracy for European than Asian men. 

  • 333.
    Ahmed, Mobyen Uddin
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Rahman, Hamidur
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Begum, Shahina
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Quality Index Analysis on Camera-based R-peak Identification Considering Movements and Light Illumination2018In: 15th International Conference on Wearable, Micro & Nano technologies for Personalized Health pHealth2018, 2018Conference paper (Refereed)
    Abstract [en]

    This paper presents a quality index (QI) analysis on R-peak extracted by a camera system considering movements and light illumination. Here, the proposed camera system is compared with a reference system named Shimmer PPG sensor. The study considers five test subjects with a 15 minutes measurement protocol, where the protocol consists of several conditions. The conditions are: normal sittings, head movements i.e., up/down/left/right/forward/backword, with light on/off and with moving flash on/off. A percentage of corrected R-peaks are calculated based on time difference in milliseconds (MS) between the R-peaks extracted both from camera-based and sensor-based systems. A comparison results between normal, movements, and lighting condition is presented as individual and group wise. Furthermore, the comparison is extended considering gender and origin of the subjects. According to the results, more than 90% R-peaks are correctly identified by the camera system with ?200 MS time differences, however, it decreases with while there is no light than when it is on. At the same time, the camera system shows more 95% accuracy for European than Asian men.

  • 334.
    Ahmed, Mobyen Uddin
    et al.
    Mälardalen University, Department of Computer Science and Electronics.
    Westin, Jerker
    Nyholm, Dag
    Dougherty, Mark
    Groth, Torgny
    A fuzzy rule-based decision support system for Duodopa treatment in Parkinson2006Conference paper (Refereed)
    Abstract [en]

    A decision support system (DSS) was implemented based on a fuzzy logic inference system (FIS) to provide assistance in dose alteration of Duodopa infusion in patients with advanced Parkinson's disease, using data from motor state assessments and dosage. Three-tier architecture with an object oriented approach was used. The DSS has a web enabled graphical user interface that presents alerts indicating non optimal dosage and states, new recommendations, namely typical advice with typical dose and statistical measurements. One data set was used for design and tuning of the FIS and another data set was used for evaluating performance compared with actual given dose. Overall goodness-of-fit for the new patients (design data) was 0.65 and for the ongoing patients (evaluation data) 0.98. User evaluation is now ongoing. The system could work as an assistant to clinical staff for Duodopa treatment in advanced Parkinson's disease.

  • 335.
    Ahmed, Ruqiyo
    et al.
    Mälardalen University, School of Business, Society and Engineering.
    Axente, Benedetta
    Mälardalen University, School of Business, Society and Engineering.
    Fathulla, Lana
    Mälardalen University, School of Business, Society and Engineering.
    The Relationship Between Business and Society: A study of corporate philanthropy within organizations2018Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    Abstract

    Date: [2018-06-01]

    Level: Bachelor thesis in Business Administration, 15 cr

    Institution: School of Business, Society and Engineering, Mälardalen University

    Authors: Ruqiyo Ahmed, Benedetta Axente, Lana Fathulla

    Title: The Relationship Between Business And Society

    Supervisor: Konstantin Lampou

    Co-assessor: Pär Blomkvist

    Keywords: CSR, Corporate Philanthropy, Core Competencies, Strategic Philanthropy

    Research Question:  How is corporate philanthropy implemented in an organization?

    Purpose: The purpose of this study is to get a deeper understanding of how organizations implement philanthropy in their business. This study further aims to answer the research question by explaining the essence of strategic philanthropy, how organizations can benefit from it and some misconceptions against philanthropy.

    Method:  This study is done through a qualitative research method. Primary data was collected by semi-structured interviews with three companies. Secondary sources was collected to complement the data collection.

    Conclusion: The findings of this paper suggests that with a strategic philanthropic approach an organization can benefit with an enhanced image and increased customer loyalty. Furthermore, it is proposed that engaging in philanthropic activities an organization will be able to attract and retain their employees. By implementing a strategic philanthropy, an organization can better choose which philanthropic issues to tackle.

  • 336.
    Ahmed, Sayidali
    Mälardalen University, School of Business, Society and Engineering.
    Kompetensutveckling i projektledning: En kompetensutvecklingshandbok för projektingenjörer2015Independent thesis Basic level (university diploma), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    This thesis presents a study of competence and knowledge needs of project engineers to be able to manage projects successfully. The aim of the thesis is to identify how to feedback competences and experiences into the project management process. The guidebook provides guidance to what a project engineer needs to focus on to become more skilled and to become a more effective project manager.

    A literature study was performed to get a better understanding of the project manager's role. A detailed study was performed on the duties of project engineers and project managers. The literature study was based on books and reports as well as an information research by the Internet. An interview with five project managers and five project engineers was conducted to compare theory with practice. Based on the respondents' answers and the results from the literature study a handbook outlining what the project engineer can do to improve their project management skills.

    The thesis concludes that competence development depends on individual motivation. Every individual have their own goals and they are stimulated by different motivational factors. Some aims high to become CEO for a company, while other are satisfied with their positions and it doesn’t mean that all project engineer / project manager strives for continuous development.

    The main question of the thesis was: "What skills are needed for project engineers to develop their skills in project management?”. The results of the thesis show that without learning from their mistakes and problems that were made in previous project and by making their own mistakes the project engineer will not develop or become a more efficient project manager. By learning from experiences from previous projects the project engineer can save significant time when facing similar problems in new projects. Recording and using this knowledge may contribute to more effective solutions and thus reducing time lost unnecessarily.

  • 337.
    Ahmed, Shakeel
    et al.
    Mälardalen University, School of Sustainable Development of Society and Technology.
    Imtiaz, Muhammad
    Mälardalen University, School of Sustainable Development of Society and Technology.
    Assessing the environmental uncontrollable elements of Swedish market that can influence and haveimpact on the presence of Lithuanian breakfast cereal producer (Palaseja) in Sweden.: A study of Swedish breakfast cereal market2009Independent thesis Advanced level (degree of Master (One Year)), 15 credits / 22,5 HE creditsStudent thesis
    Abstract [en]

    Problem:

    Palaseja is considering Sweden as a prospect market to enter and operate so, a study of Swedish

    business environment and its uncontrollable elements is required for Palaseja to serve this purpose

    effectively.

    Method:

    Thesis has followed a combination of exploratory & descriptive research and a qualitative approach

    has been applied. Both primary and secondary data have been gathered, primary data was gathered

    through interviews from retail stores' officials and Palaseja's sales manager.

    Conclusion:

    In this study, different environmental uncontrollable elements of Swedish market have been explored

    to find out how they can influence a new entrant Palaseja in Sweden. There are a few legal

    requirements for Palaseja to enter in food market of Sweden. Economic forces are facing a little slow

    down effect due to recent global economic slump but are quite encouraging for any new company

    entering Sweden in the long run. Breakfast cereal products that Palaseja produces have found to be a

    common part of cultural breakfast habits and huge consumption of breakfast cereal per capita also

    seems to be encouraging for new comers in this industry. Competitive forces have been found to be

    extremely challenging and quite discouraging in some way. The country of origin effect seems to be

    not so strong in Sweden although brand recognition of Palaseja is likely to cause some trouble to

    Palaseja's success.

  • 338.
    Ahmed, Shehzad
    et al.
    Mälardalen University, School of Business, Society and Engineering.
    Moosavi, Zahra
    Mälardalen University, School of Business, Society and Engineering.
    Factors Influencing the Cell Phone Brand Loyalty of Swedish Generation Y.2013Independent thesis Advanced level (degree of Master (One Year)), 10 credits / 15 HE creditsStudent thesis
  • 339.
    Ahmed, Zeinab
    Mälardalen University, School of Innovation, Design and Engineering.
    Material och Lagerstyrningssystem2019Independent thesis Basic level (university diploma), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    Previously, Husmuttern had difficulty controlling inventory levels and purchase orders. This had a negative impact on production. The company had no effective system to plan and control inventory levels; material and inventory management was performed by an external supplier. The transport of raw materials was planned every other day and failed to take into account the vehicle’s load capacity, it has affected transport costs and the environment.

    The purpose of the thesis work is to identify problems and provide recommendations, supported by theories of how an efficient material planning system can be implemented, to increase profitability, reduce transport costs, environmental impacts, as well as achieve balance between material flow and demand.

    The results showed that using an effective material planning system, both stock levels and purchase orders are controlled. The student tested using the order point method to control stock levels and purchase orders.

  • 340.
    Ahrén, Christina
    et al.
    Mälardalen University, School of Innovation, Design and Engineering.
    Nyblad, Ida
    Mälardalen University, School of Innovation, Design and Engineering.
    Investigating DRAM bank partitioning2018Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    We have investigated the page coloring technique bank partitioning and if it can be applied on commercial hardware platforms to reduce execution time jitter for specific tasks. We have also investigated how to alter execution times using bank partitioning. Unpredictable latency created by execution time jitter is a problem in real-time computing on commercial hardware platforms. We have run experiments that try to prove that the bank partitioning method we use alters the execution time and that thrashing occurs in the main memory if we run multiple instances of a workload. We receive significant changes in execution times when using bank partitioning and we can determine that thrashing occurs. However, due to the lack of the ability to measure the hardware performance counter for row buffer misses, we cannot determine if thrashing occurs in the main memory level. Since we cannot determine when, or if thrashing occurs in the main memory we find that we cannot reduce execution time jitter on the two systems that we have tested using bank partitioning on. We also find that execution times of specific tasks can be altered by reducing the number of bank bins associated with the specific task. The execution time of the task is increased if we reduce the number of bins associated with it.

  • 341.
    Ahvenlampi Svensson, Amanda
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Exploring challenges in a verification process - when adapting production processes to new environmental requirements2016Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    The requirements on the products and production processes within the manufacturing industry are continuously increasing according to environmental standards. The new requirements are coming from a growing awareness of what our planet can provide for example by the global challenge of climate change. The industry needs to reduce energy consumption and waste to meet the upcoming requirements.

    One of the processes with high environmental impact in a discrete manufacturing industry is the paint shop. Surface treatment is also of great importance to maintain a high quality product. In scientific literature, technological risk is one of the barriers in implementing environmental conscious manufacturing. Therefore the area of sustainable operations management needs building bridges with other functions and disciplines such as economics, strategies and behavioral sciences in order to manage the transitions. The supply of competence around paint shops today is usually provided by suppliers and other sources within the industry and to make the collaboration to work is essential. In this process of collaboration with external sources, substantial measurements are required to maintain the desirable quality. In order to ensure the competence of testing the quality eventuate when switching technology at a pre-treatment line, this report sets out to explore what the challenges to be taken into consideration are when to assure the product- and- process quality. To respond to this question, a multiple case study is conducted during spring 2016 where the phenomenon to study is the change process and the unit of analysis is the challenges that can be faced during the verification process. The case studied is automotive companies located in Sweden which are producing components for heavy duty vehicles. Data collection is performed by studying documents, participatory observations and semi-structured interviews. The results will give insights to academia on what challenges that are occurring during the verification process of implementing new and cleaner technologies. The conclusions are drawn upon the literature and the empirical results. The managerial implications are to increase the awareness of any potential barriers in the verification process in order to be prepared for managing the technological change process.

  • 342.
    Ahy, Nathaniel
    et al.
    Mälardalen University, School of Education, Culture and Communication.
    Sierra, Mikael
    Mälardalen University, School of Education, Culture and Communication.
    Implied Volatility Surface Approximation under a Two-Factor Stochastic Volatility Model2018Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    Due to recent research disproving old claims in financial mathematics such as constant volatility in option prices, new approaches have been incurred to analyze the implied volatility, namely stochastic volatility models. The use of stochastic volatility in option pricing is a relatively new and unexplored field of research with a lot of unknowns, where new answers are of great interest to anyone practicing valuation of derivative instruments such as options. With both single and two-factor stochastic volatility models containing various correlation structures with respect to the asset price and differing mean-reversions of variance the question arises as to how these values change their more observable counterpart: the implied volatility. Using the semi-analytical formula derived by Chiarella and Ziveyi, we compute European call option prices. Then, through the Black–Scholes formula, we solve for the implied volatility by applying the bisection method. The implied volatilities obtained are then approximated using various models of regression where the models’ coefficients are determined through the Moore–Penrose pseudo-inverse to produce implied volatility surfaces for each selected pair of correlations and mean-reversion rates. Through these methods we discover that for different mean-reversions and correlations the overall implied volatility varies significantly and the relationship between the strike price, time to maturity, implied volatility are transformed.

  • 343.
    Aisa, J.
    et al.
    Universidad de Zaragoza, Zaragoza, Spain .
    Fotouhi, Hossein
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Villarroel, J. L.
    Universidad de Zaragoza, Zaragoza, Spain .
    Almeida, L.
    University of Porto, Porto, Portugal.
    Soft real-time traffic communication in loaded Wireless Mesh Networks2016In: IEEE International Workshop on Factory Communication Systems - Proceedings, WFCS, 2016, article id Article number 7496503Conference paper (Refereed)
    Abstract [en]

    Industrial applications have been shifting towards wireless multi-hop networks in recent years due to their lower cost of deployment and reconfiguration compared with their wired counterparts. These wireless networks usually must support real-time communication to meet the application requirements. For this reason, Wireless Mesh Networks (WMNs) are potential candidates for industrial applications as they support a fixed infrastructure of static nodes for relaying packets. To meet the application demands, we modify the wireless chain network protocol (WICKPro) to support soft real-time traffic in WMNs with chain topologies over IEEE 802.11. We employ tele-operation of mobile robots as our case study, and perform extensive simulation and laboratory experiments. We show that the data delivery ratio is increased up to 42% in a scenario with 7 nodes, when the maximum end-to-end delay tolerated by the application is doubled. This is particularly suited to soft real-time applications that can trade longer delays by higher reliability. Moreover, when compared with a distributed priority-based token-passing protocol (RT-WMP), the lower overhead of WICKPro allows, in an error-free scenario, obtaining a throughput improvement of 33.42% on average.

  • 344.
    Aisa, Jesus
    et al.
    Universidad de Zaragoza, Zaragoza, Spain.
    Fotouhi, Hossein
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Almeida, Luis
    University of Porto, Portugal.
    Villarroel, José Luis
    Universidad de Zaragoza, Zaragoza, Spain.
    DoTHa - A Double-threshold Hand-off Algorithm for Managing Mobility in Wireless Mesh Networks2016In: 21st IEEE Conference on Emerging Technologies and Factory Automation ETFA'16, 2016, article id 7733511Conference paper (Refereed)
    Abstract [en]

    Wireless communication will play an increasingly important role in future factory automation and process control, where the presence of mobile autonomous devices is expected to grow. However, wireless links are prone to errors due to shadowing and multi-path fading, which is even more severe in dynamic environments. These problems can be attenuated by using a mesh backbone to which mobile node connect to, using a hand-off algorithm. This solution is particularly important under real-time requirements typically found in factory automation. In this paper, we devise the Double-Threshold Hand-off (DoTHa) algorithm, a novel hand-off mechanism that triggers a hand-off in various environmental conditions. As a case study, we carry out the tele-operation of a mobile robot through a wireless mesh network in an indoor setting, using a wireless chain network protocol (WICKPro-SRT) that supports soft real-time traffic. We empirically compared DoTHa with two existing hand-off algorithms based on single and double hysteresis margin. The results revealed that DoTHa achieves Data Delivery Ratio (DDR) close to 100% whereas the single hysteresis-based hand-off suffers from frequent disconnections, dropping DDR to 88%. The double hysteresis-based hand-off shows higher ping-pong effect than DoTHa, doubling the number of hand-offs in some scenarios.

  • 345.
    Ajamlou, Anita
    et al.
    Mälardalen University, School of Sustainable Development of Society and Technology.
    Ekberg, Andreas
    Mälardalen University, School of Sustainable Development of Society and Technology.
    Gülünay, Michel
    Mälardalen University, School of Sustainable Development of Society and Technology.
    Revisionspliktens avskaffande: Påverkan på revisionsbyråer och deras marknadsföring2011Independent thesis Advanced level (degree of Master (One Year)), 15 credits / 22,5 HE creditsStudent thesis
    Abstract [sv]

    Syftet med denna uppsats är att ta reda på hur vissa svenska revisionsbyråer påverkats av avskaffandet av revisionsplikten. Studien medför även hur svenska revisionsbyråer ska agera för att behålla sina nuvarande kunder.

  • 346.
    Ajmaya, Davi
    et al.
    Mälardalen University, School of Innovation, Design and Engineering.
    Eklund, Dennis
    Mälardalen University, School of Innovation, Design and Engineering.
    Machine learning based pedestrian event monitoring using IMU and GPS2018Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    Understanding the behavior of pedestrians in road transportation is critical to maintain a safe en- vironment. Accidents on road transportation are one of the most common causes of death today. As autonomous vehicles start to become a standard in our society, safety on road transportation becomes increasingly important. Road transportation is a complex system with a lot of dierent factors. Identifying risky behaviors and preventing accidents from occurring requires better under- standing of the behaviors of the dierent persons involved. In this thesis the activities and behavior of a pedestrian is analyzed. Using sensor data from phones, eight dierent events of a pedestrian are classied using machine learning algorithms. Features extracted from phone sensors that can be used to model dierent pedestrian activities are identied. Current state of the art literature is researched to nd relevant machine learning algorithms for a classication model. Two models are implemented using two dierent machine learning algorithms: Articial Neural Network and Hid- den Markov Model. Two dierent experiments are conducted where phone sensor data is collected and classied using the models, achieving a classication accuracy of up to 93%.

  • 347.
    Akan, Batu
    Mälardalen University, School of Innovation, Design and Engineering.
    Human Robot Interaction Solutions for Intuitive Industrial Robot Programming2012Licentiate thesis, comprehensive summary (Other academic)
    Abstract [en]

    Over the past few decades the use of industrial robots has increased the efficiency as well as competitiveness of many companies. Despite this fact, in many cases, robot automation investments are considered to be technically challenging. In addition, for most small and medium sized enterprises (SME) this process is associated with high costs. Due to their continuously changing product lines, reprogramming costs are likely to exceed installation costs by a large margin. Furthermore, traditional programming methods for industrial robots are too complex for an inexperienced robot programmer, thus assistance from a robot programming expert is often needed.  We hypothesize that in order to make industrial robots more common within the SME sector, the robots should be reprogrammable by technicians or manufacturing engineers rather than robot programming experts. In this thesis we propose a high-level natural language framework for interacting with industrial robots through an instructional programming environment for the user.  The ultimate goal of this thesis is to bring robot programming to a stage where it is as easy as working together with a colleague.In this thesis we mainly address two issues. The first issue is to make interaction with a robot easier and more natural through a multimodal framework. The proposed language architecture makes it possible to manipulate, pick or place objects in a scene through high level commands. Interaction with simple voice commands and gestures enables the manufacturing engineer to focus on the task itself, rather than programming issues of the robot. This approach shifts the focus of industrial robot programming from the coordinate based programming paradigm, which currently dominates the field, to an object based programming scheme.The second issue addressed is a general framework for implementing multimodal interfaces. There have been numerous efforts to implement multimodal interfaces for computers and robots, but there is no general standard framework for developing them. The general framework proposed in this thesis is designed to perform natural language understanding, multimodal integration and semantic analysis with an incremental pipeline and includes a novel multimodal grammar language, which is used for multimodal presentation and semantic meaning generation.

  • 348.
    Akan, Batu
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Planning and Sequencing Through Multimodal Interaction for Robot Programming2014Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Over the past few decades the use of industrial robots has increased the efficiency as well as the competitiveness of several sectors. Despite this fact, in many cases robot automation investments are considered to be technically challenging. In addition, for most small and medium-sized enterprises (SMEs) this process is associated with high costs. Due to their continuously changing product lines, reprogramming costs are likely to exceed installation costs by a large margin. Furthermore, traditional programming methods of industrial robots are too complex for most technicians or manufacturing engineers, and thus assistance from a robot programming expert is often needed. The hypothesis is that in order to make the use of industrial robots more common within the SME sector, the robots should be reprogrammable by technicians or manufacturing engineers rather than robot programming experts. In this thesis, a novel system for task-level programming is proposed. The user interacts with an industrial robot by giving instructions in a structured natural language and by selecting objects through an augmented reality interface. The proposed system consists of two parts: (i) a multimodal framework that provides a natural language interface for the user to interact in which the framework performs modality fusion and semantic analysis, (ii) a symbolic planner, POPStar, to create a time-efficient plan based on the user's instructions. The ultimate goal of this work in this thesis is to bring robot programming to a stage where it is as easy as working together with a colleague.This thesis mainly addresses two issues. The first issue is a general framework for designing and developing multimodal interfaces. The general framework proposed in this thesis is designed to perform natural language understanding, multimodal integration and semantic analysis with an incremental pipeline. The framework also includes a novel multimodal grammar language, which is used for multimodal presentation and semantic meaning generation. Such a framework helps us to make interaction with a robot easier and more natural. The proposed language architecture makes it possible to manipulate, pick or place objects in a scene through high-level commands. Interaction with simple voice commands and gestures enables the manufacturing engineer to focus on the task itself, rather than the programming issues of the robot. The second issue addressed is due to inherent characteristics of communication with the use of natural language; instructions given by a user are often vague and may require other actions to be taken before the conditions for applying the user's instructions are met. In order to solve this problem a symbolic planner, POPStar, based on a partial order planner (POP) is proposed. The system takes landmarks extracted from user instructions as input, and creates a sequence of actions to operate the robotic cell with minimal makespan. The proposed planner takes advantage of the partial order capabilities of POP to execute actions in parallel and employs a best-first search algorithm to seek the series of actions that lead to a minimal makespan. The proposed planner can also handle robots with multiple grippers, parallel machines as well as scheduling for multiple product types.

  • 349.
    Akan, Batu
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Ameri E., Afsh
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Çürüklü, Baran
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Towards Creation of Robot Programs Through User InteractionManuscript (preprint) (Other academic)
    Abstract [en]

    This paper proposes a novel system for task-level programming of industrial robots. The user interacts with an industrial robot by giving instructions in a structured natural language and by selecting objects through an augmented reality interface. The proposed system consists of two parts. First, a multimodal framework that provides a natural language interface to the user. This framework performs modality fusion, semantic analysis and helps the user to interact with the system easier and more naturally. The proposed language architecture makes it possible to manipulate, pick or place objects in a scene through high-level commands. The second component is the POPStar planner, which is based on partial order planner (POP), that takes landmarks extracted from user instructions as input, and creates a sequence of actions to operate the robotic cell with minimal makespan. The proposed planner takes advantage of partial order capabilities of POP to plan execution of actions in parallel and employs a best-first search algorithm to seek a series of actions that lead to a minimal makespan. The proposed planner can as well handle robots with multiple grippers, and  parallel machines. Using different topologies for the landmark graphs, we show that it is possible to create schedules for changing object types, which are processed in different stages in the robot cell. Results show that the proposed system can create and adapt schedules for robot cells with changing product types in low volume production based on the user's instructions.

  • 350.
    Akan, Batu
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Ameri E., Afshin
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Curuklu, Baran
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Scheduling for Multiple Type Objects Using POPStar Planner2014In: Proceedings of the 19th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA'14), Barcelona, Spain, September, 2014, 2014, p. Article number 7005148-Conference paper (Refereed)
    Abstract [en]

    In this paper, scheduling of robot cells that produce multiple object types in low volumes are considered. The challenge is to maximize the number of objects produced in a given time window as well as to adopt the  schedule for changing object types. Proposed algorithm, POPStar, is based on a partial order planner which is guided by best-first search algorithm and landmarks. The best-first search, uses heuristics to help the planner to create complete plans while minimizing the makespan. The algorithm takes landmarks, which are extracted from user's instructions given in structured English as input. Using different topologies for the landmark graphs, we show that it is possible to create schedules for changing object types, which will be processed in different stages in the robot cell. Results show that the POPStar algorithm can create and adapt schedules for robot cells with changing product types in low volume production.

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