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  • 301.
    Ahmadzadeh, Farzaneh
    Islamic Azad University of Karaj Branch, Karaj, Tehran, Iran .
    Change point detection with multivariate control charts by artificial neural network2009In: International Journal of Advanced Manufacturing Technology IJAMT, ISSN 0268-3768, p. 1-12Article in journal (Refereed)
  • 302.
    Ahmadzadeh, Farzaneh
    Islamic Azad University, Iran.
    Diagnosing the Cause and Its Timing of Changes in Multivariate Process Mean Vector From Quality Control Charts Using Artificial Neural Network2011In: World Academy of Science, Engineering and Technology: An International Journal of Science, Engineering and Technology, ISSN 2010-376X, E-ISSN 2070-3740, Vol. 5, no 6, p. 212-217Article in journal (Refereed)
    Abstract [en]

    Quality control charts are very effective in detecting out of control signals but when a control chart signals an out of control condition of the process mean, searching for a special cause in the vicinity of the signal time would not always lead to prompt identification of the source(s) of the out of control condition as the change point in the process parameter(s) is usually different from the signal time. It is very important to manufacturer to determine at what point and which parameters in the past caused the signal. Early warning of process change would expedite the search for the special causes and enhance quality at lower cost. In this paper the quality variables under investigation are assumed to follow a multivariate normal distribution with known means and variance-covariance matrix and the process means after one step change remain at the new level until the special cause is being identified and removed, also it is supposed that only one variable could be changed at the same time. This research applies artificial neural network (ANN) to identify the time the change occurred and the parameter which caused the change or shift. The performance of the approach was assessed through a computer simulation experiment. The results show that neural network performs effectively and equally well for the whole shift magnitude which has been considered.

  • 303.
    Ahmadzadeh, Farzaneh
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Multi criteria decision making with Evidential Reasoning under uncertainty2016In: IEEE International Conference on Industrial Engineering and Engineering Management, 2016, p. 1534-1538Conference paper (Refereed)
    Abstract [en]

    Many decision problems have more than one objective that need to be dealt with simultaneously. Moreover, because of the qualitative nature of the most of real world problem it is an inevitable activity and very important to interpret and present the uncertain information for making effective decision. The Evidential Reasoning (ER) approach which is one of the latest development within multi criteria decision making (MCDM) seems to be the best fit to synthesize both qualitative and quantitative data under uncertainty. To support this claim, two case studies were tested to illustrate the application of ER for prioritization and ranking of decision alternative to support decision process even with uncertain information. The importance of having a better structured decision process is essential for the success of any organization, so it can be applied widely in most of real world problem dealing with making effective decision.

  • 304.
    Ahmadzadeh, Farzaneh
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Ranking of Two Multi Criteria Decision Making Cases with Evidential Reasoning under Uncertainty2017In: Advances in Science, Technology and Engineering Systems Journal V2(3) ASTESJ-V2(3), ISSN 2415-6698, Vol. 2, no 3, p. 1059-1063Article in journal (Refereed)
    Abstract [en]

    Many decision problems have more than one objective that need to be dealt with simultaneously. Moreover, because of the qualitative nature of the most of real world problem it is an inevitable activity and very important to interpret and present the uncertain information for making effective decision. The Evidential Reasoning (ER) approach which is one of the latest development within multi criteria decision making (MCDM) seems to be the best fit to synthesize both qualitative and quantitative data under uncertainty. To support this claim, two case studies were tested to illustrate the application of ER for prioritization and ranking of decision alternative to support decision process even with uncertain information. The overall goal of the first case study is to identify and prioritize factors that can be considered maintenance-related waste within the automotive manufacturing industry. The result after applying ER shows “inadequate resources” and “weather /indoor climate,” respectively, are the highest and lowest average scores for creating maintenance-related waste. This prioritization methodology can be used as a tool to create awareness for managers seeking to reduce or eliminate maintenance-related waste. The aim of the second case study is to look at the possibility of having a new approach for sustainable design. So through a literature review six design strategies were taken into consideration in order to develop a new approach based on all advantages (sustainable factors) of the six approaches. For ranking and finding out about the most important factors the evidential reasoning (ER) approach is used. Based on ER all the important factors, apart from the one collected from interviews are a part of eco-design. So it means among all strategies eco-design is the most dominant strategy in term of environment. However two of the important factors are not found in any strategy but in interviews. These factors can be used as the building blocks for a new approach. The importance of having a better structured decision process is essential for the success of any organization, so it can be applied widely in most of real world problem dealing with making effective decision.

  • 305.
    Ahmadzadeh, Farzaneh
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Bengtsson, Marcus
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Classification of Maintenance-Related Waste Based on Human Factors2015In: 22nd International Annual EurOMA Conference EurOMA15, Neuchâtel, Switzerland, 2015Conference paper (Refereed)
    Abstract [en]

    The goal of this research is to identify and classify factors creating maintenance-related waste. A workshop study has been performed in order to identify root-causes for maintenance-related waste. In total, 16 categories were found in the analysis and it is concluded that these are heavily reliant on human factors as a root- or major contributory cause. These, together with factors based on a literature review have been incorporated into a classification model. The model can be used in creating awareness in, as well as provide a basic framework for decision making of, which waste to target for elimination.

  • 306.
    Ahmadzadeh, Farzaneh
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Bengtsson, Marcus
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Using evidential reasoning approach for prioritization of maintenance-related waste caused by human factors-a case study2017In: The International Journal of Advanced Manufacturing Technology, ISSN 0268-3768, E-ISSN 1433-3015, Vol. 90, no 9-12, p. 2761-2775Article in journal (Refereed)
    Abstract [en]

    The reduction and elimination of maintenance-related waste is receiving increasing attention because of the negative effect of such waste on production costs. The overall goal of this research is to identify and prioritize factors that can be considered maintenance-related waste within the automotive manufacturing industry. Five manufacturing companies participated in a workshop to identify root causes of maintenance-related waste; 16 categories were found. The identified factors were heavily reliant on human factors as a root or major contributory cause at different levels affecting performance and productivity. For prioritization, the evidential reasoning (ER) approach which is one of the latest developments in multi-criteria decision-making is applied. A basic tree structure necessary for ER assessment is developed based on the workshop results as well as literature on human factors. Then, a survey on basic attributes at the lowest level of this tree is designed and performed at one of the companies participating in the workshop. The application of ER shows that, on an overall level, "management condition" is in first order and "maintainer condition" and "working condition" are in second and third order respectively as the worst cases for creating maintenance-related waste. On the most delimited level "inadequate resources" and "weather/indoor climate" have the highest and lowest average scores respectively in ER ranking or prioritization. This methodology with its resulting ranking can be used as a tool to create awareness for managers seeking to reduce or eliminate maintenance-related waste.

  • 307.
    Ahmadzadeh, Farzaneh
    et al.
    Luleå University of Technology, Sweden.
    Golshani Asl, Aliakbar
    Luleå University of Technology, Sweden.
    Risk Prioritization Based on Health, Safety and Environmental Factors by Using Fuzzy FMEA2013In: International Journal of Mining, Metallurgy & Mechanical Engineering, ISSN 2320-4052, Vol. 1, no 4, p. 233-237Article in journal (Refereed)
    Abstract [en]

    Failure Mode and Effects Analysis is assessing technique which relies to the rule of preventing failure, which is used to identify potential hazards. This method is used with minimum risks to predict the problems and deficits in design stage or development of the processes and services in organizations. The methods main principal is based on multiplying three main parameters: severity, occurrence, detection. This method with all the advantages still has minor disadvantages that in this paper attempts has been made to eliminate these deficiencies by fuzzification. Results show that fuzzy FMEA will enables us to evaluate situations correctly and precisely.

  • 308.
    Ahmadzadeh, Farzaneh
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Jederström, Kathrina
    Mälardalen University.
    Plahn, Maria
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.
    Olsson, Anna
    Mälardalen University.
    Foyer, Isabell
    Mälardalen University.
    AN INVESTIGATION OF THE MOST IMPORTANT FACTORS FOR SUSTAINABLE PRODUCT DEVELOPMENT USING EVIDENTIAL REASONING2017In: Numerical Algebra, Control and Optimization, ISSN 2155-3289, E-ISSN 2155-3297, Vol. 7, no 4, p. 435-455Article in journal (Refereed)
    Abstract [en]

    Those working in product development need to consider sustain ability, being careful not to compromise the future generations ability to satisfy its needs. Several strategies guide companies towards sustainability. This paper studies six of these strategies: eco-design, green design, cradle-to-cradle, design for environment, zero waste, and life cycle approaches. Based on a literature review and semi-structured interviews, it identifies 22 factors of sustainability from the perspective of manufacturers. The purpose is to determine which are the most important and to use them as a foundation for a new design strategy. A survey based on the 22 factors was given to people working with product development; they graded each factor by importance. The resulting qualitative data were analyzed using evidential reasoning. The analysis found the factors minimize use of toxic substances, increase competitiveness, economic benefits, reduce material usage, material selection, reduce emissions, and increase product functionality are more important and should serve as the foundation for a new approach to sustainable product development.

  • 309.
    Ahmadzadeh, Farzaneh
    et al.
    Luleå University of Technology, Luleå, Sweden .
    Lundberg, J.
    Luleå University of Technology, Luleå, Sweden .
    Remaining useful life prediction of grinding mill liners using an artificial neural network2013In: Minerals Engineering, ISSN 0892-6875, E-ISSN 1872-9444, Vol. 53, p. 1-8Article in journal (Refereed)
    Abstract [en]

    Knowing the remaining useful life of grinding mill liners would greatly facilitate maintenance decisions. Now, a mill must be stopped periodically so that the maintenance engineer can enter, measure the liners' wear, and make the appropriate maintenance decision. As mill stoppage leads to heavy production losses, the main aim of this study is to develop a method which predicts the remaining useful life of the liners, without needing to stop the mill. Because of the proven ability of artificial neural networks (ANNs) to recognize complex relationships between input and output variables, as well as its adaptive and parallel information-processing structure, an ANN has been designed based on the various process parameters which influence wear of the liners. The process parameters were considered as inputs while remaining height and remaining life of the liners were outputs. The results show remarkably high degree of correlation between the input and output variables. The performance of the neural network model is very consistent for data used for training (seen) and testing (unseen).

  • 310.
    Ahmadzadeh, Farzaneh
    et al.
    Luleå University of Technology, Sweden.
    Lundberg, Jan
    Luleå University of Technology, Sweden.
    Application of multi regressive linear model and neural network for wear prediction of grinding mill liners2013In: International Journal of Advanced Computer Sciences and Applications, ISSN 2158-107X, E-ISSN 2156-5570, Vol. 4, no 5, p. 52-58Article in journal (Refereed)
    Abstract [en]

    The liner of an ore grinding mill is a critical component in the grinding process, necessary for both high metal recovery and shell protection. From an economic point of view, it is important to keep mill liners in operation as long as possible, minimising the downtime for maintenance or repair. Therefore, predicting their wear is crucial. This paper tests different methods of predicting wear in the context of remaining height and remaining life of the liners. The key concern is to make decisions on replacement and maintenance without stopping the mill for extra inspection as this leads to financial savings. The paper applies linear multiple regression and artificial neural networks (ANN) techniques to determine the most suitable methodology for predicting wear. The advantages of the ANN model over the traditional approach of multiple regression analysis include its high accuracy.

  • 311.
    Ahmadzadeh, Farzaneh
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation. Luleå University of Technology, Luleå, Sweden.
    Lundberg, Jan
    Luleå University of Technology, Luleå, Sweden.
    Remaining useful life estimation: Review2014In: International Journal of Systems Assurance Engineering and Management, ISSN 0975-6809, E-ISSN 0976-4348, Vol. 5, no 4, p. 461-474Article, book review (Other academic)
    Abstract [en]

    This paper reviews the recent modelling developments in estimating the remaining useful life (RUL) of industrial systems. The RUL estimation models are categorized into experimental, data driven, physics based and hybrid approaches. The paper reviews some typical approaches and discusses their advantages and disadvantages. According to the literature, the selection of the best model depends on the level of accuracy and availability of data. In cases of quick estimations which are less accurate, the data driven method is preferred, while the physics based approach is applied when the accuracy of estimation is important.

  • 312.
    Ahmadzadeh, Farzaneh
    et al.
    Luleå University of Technology, Luleå, Sweden.
    Lundberg, Jan
    Luleå University of Technology, Luleå, Sweden.
    Strömberg, Thomas
    Luleå University of Technology, Luleå, Sweden.
    Multivariate process parameter change identification by neural network2013In: The International Journal of Advanced Manufacturing Technology, ISSN 0268-3768, E-ISSN 1433-3015, Vol. 69, no 9-12, p. 2261-2268Article in journal (Refereed)
    Abstract [en]

    Whenever there is an out-of-control signal in process parameter control charts, maintenance engineers try to diagnose the cause near the time of the signal which does not always lead to prompt identification of the source(s) of the out-of-control condition, and this in some cases yields to extremely high monetary loses for the manufacturer owner. This paper applies multivariate exponentially weighted moving average (MEWMA) control charts and neural networks to make the signal identification more effective. The simulation of this procedure shows that this new control chart can be very effective in detecting the actual change point for all process dimension and all shift magnitudes considered. This methodology can be used in manufacturing and process industries to predict change points and expedite the search for failure causing parameters, resulting in improved quality at reduced overall cost. This research shows development of MEWMA by usage of neural network for identifying the step change-point and the variable responsible for the change in the process mean vector.

  • 313.
    Ahmed, Arslan
    et al.
    Mälardalen University. Mälardalen University, School of Sustainable Development of Society and Technology.
    Pang, Zhaohua
    Mälardalen University. Mälardalen University, School of Sustainable Development of Society and Technology.
    CORPORATE CULTURE IN AN INTERNATIONAL JOINT VENTURE - A case study of Sony Ericsson2009Independent thesis Advanced level (degree of Master (One Year)), 15 credits / 22,5 HE creditsStudent thesis
    Abstract [en]

    Research Problem: To what extent the corporate culture of an international joint venture resembles the organizational and national culture of its parent firms?

    Purpose: The purpose of this research is to study and explain the organizational and national culture of the partner companies that are involved in the international joint venture and finds out the extent to which the corporate culture that is embedded in the joint venture possess a resemblance with its parent's culture.

    Method: Our research is qualitative in nature and is based upon the case study and the secondary information gathered during the research. We have also taken into account some primary information through conducting three semi-structured interviews from each of the company involved in the joint venture. All the information collected during the course of our research has been analyzed in such a manner that has eventually led us to a formidable conclusion.

    Conclusion: After the analysis of results, both from the interviews and the secondary information, we came to a conclusion that the corporate culture at the joint venture possess some similarities with the national and organizational cultures of its parent firms and this likeness depends upon the location of origin of the joint venture and the employees working in it.   

  • 314.
    Ahmed, Athar Nadeem
    Mälardalen University, School of Innovation, Design and Engineering.
    Wireless inertial measurement unit for industrial robotic arm2013Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
  • 315.
    Ahmed, B. S.
    et al.
    Istituto Dalle Molle di Studi Sull'Intelligenza Artificiale (IDSIA), Manno-Lugano, Switzerland.
    Sahib, M. A.
    Software and Informatics Engineering Department, Engineering College, Salahaddin University - Erbil, Iraq.
    Gambardella, L. M.
    Istituto Dalle Molle di Studi Sull'Intelligenza Artificiale (IDSIA), Manno-Lugano, Switzerland.
    Afzal, Wasif
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Zamli, K. Z.
    IBM Centre of Excellence, Faculty of Computer Systems and Software Engineering, Universiti Malaysia Pahang Lebuhraya Tun Razak, Kuantan, Pahang Darul Makmur, Malaysia.
    Optimum design of PIλDμ controller for an automatic voltage regulator system using combinatorial test design2016In: PLoS ONE, ISSN 1932-6203, E-ISSN 1932-6203, Vol. 11, no 11, article id e0166150Article in journal (Refereed)
    Abstract [en]

    Combinatorial test design is a plan of test that aims to reduce the amount of test cases systematically by choosing a subset of the test cases based on the combination of input variables. The subset covers all possible combinations of a given strength and hence tries to match the effectiveness of the exhaustive set. This mechanism of reduction has been used successfully in software testing research with t-way testing (where t indicates the interaction strength of combinations). Potentially, other systems may exhibit many similarities with this approach. Hence, it could form an emerging application in different areas of research due to its usefulness. To this end, more recently it has been applied in a few research areas successfully. In this paper, we explore the applicability of combinatorial test design technique for Fractional Order (FO), Proportional-Integral-Derivative (PID) parameter design controller, named as FOPID, for an automatic voltage regulator (AVR) system. Throughout the paper, we justify this new application theoretically and practically through simulations. In addition, we report on first experiments indicating its practical use in this field. We design different algorithms and adapted other strategies to cover all the combinations with an optimum and effective test set. Our findings indicate that combinatorial test design can find the combinations that lead to optimum design. Besides this, we also found that by increasing the strength of combination, we can approach to the optimum design in a way that with only 4-way combinatorial set, we can get the effectiveness of an exhaustive test set. This significantly reduced the number of tests needed and thus leads to an approach that optimizes design of parameters quickly. © 2016 Ahmed et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

  • 316.
    Ahmed, Bestoun
    et al.
    Istituto Dalle Molle di Studi sullIntelligenza Artificiale (IDSIA), Switzerland.
    Gambardella, Luca
    Istituto Dalle Molle di Studi sullIntelligenza Artificiale (IDSIA), Switzerland.
    Afzal, Wasif
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Zamli, Kamal
    University Malaysia Pahang, Gambang, Malaysia.
    Handling Constraints in Combinatorial Interaction Testing in the Presence of Multi Objective Particle Swarm and Multithreading2017In: Information and Software Technology, ISSN 0950-5849, E-ISSN 1873-6025, Vol. 86, no 01, p. 20-36Article in journal (Refereed)
    Abstract [en]

    Combinatorial strategies have received a lot of attention lately as a result of their diverse applications in areas of research, particularly in software engineering. In its simple form, a combinatorial strategy can reduce several input parameters (configurations) of a system into a small set of these parameters based on their interaction (combination). However, in practice, the input configurations of software systems are subjected to constraints, especially highly configurable systems. To implement this feature within a strategy, many difficulties arise for construction. While there are many combinatorial interaction testing strategies nowadays, few of them support constraints. This paper presents a new strategy, called Octopus to construct a combinatorial interaction test suites with the presence of constraints. The design and algorithms are provided in the paper in detail. The strategy is inspired by the behaviour of octopus to search for the optimal solution using multi-threading mechanism. To overcome the multi judgement criteria for an optimal solution, the multi-objective particle swarm optimisation is used. The strategy and its algorithms are evaluated extensively using different benchmarks and comparisons. The evaluation results showed the efficiency of each algorithm in the strategy. The benchmarking results also showed that Octopus can generate test suites efficiently as compared to state-of-the-art strategies.

  • 317.
    Ahmed, Bestoun
    et al.
    Czech Technical University, Czech Republic.
    Zamli, Kamal
    University Malaysia Pahang, Gambang, Malaysia..
    Afzal, Wasif
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Bures, Miroslav
    Czech Technical University, Czech Republic.
    Constrained Interaction Testing: A Systematic Literature Study2017In: IEEE Access, E-ISSN 2169-3536, IEEE Access, ISSN 2169-3536, Vol. PP, no 99Article, book review (Other academic)
    Abstract [en]

    Interaction testing can be used to effectively detect faults that are otherwise difficult to find by other testing techniques. However, in practice, the input configurations of software systems are subjected to constraints, especially in the case of highly configurable systems. Handling constraints effectively and efficiently in combinatorial interaction testing is a challenging problem. Nevertheless, researchers have attacked this challenge through different techniques, and much progress has been achieved in the past decade. Thus, it is useful to reflect on the current achievements and shortcomings and to identify potential areas of improvements. This paper presents the first comprehensive and systematic literature study to structure and categorize the research contributions for constrained interaction testing. Following the guidelines of conducting a literature study, the relevant data is extracted from a set of 103 research papers belonging to constrained interaction testing. The topics addressed in constrained interaction testing research are classified into four categories of constraint test generation, application, generation & application and model validation studies. The papers within each of these categories are extensively reviewed. Apart from answering several other research questions, this study also discusses the applications of constrained interaction testing in several domains such as software product lines, fault detection & characterization, test selection, security and GUI testing. The study ends with a discussion of limitations, challenges and future work in the area.

  • 318.
    Ahmed Farah, Farah
    Mälardalen University, School of Sustainable Development of Society and Technology.
    Studenters förtroende för E-handel.2008Independent thesis Basic level (degree of Bachelor), 10 points / 15 hpStudent thesis
  • 319.
    Ahmed Ibrahim, Abdulla
    et al.
    Mälardalen University, School of Sustainable Development of Society and Technology.
    Andersson, Alexis
    Mälardalen University, School of Sustainable Development of Society and Technology.
    Aggregerade kundmissnöjen i informationssystem – En fallstudie av Nordea Bank2012Independent thesis Advanced level (degree of Master (One Year)), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    Abstract“Aggregate complaints in banks MIS”

    Date:                       June 8th 2012

    Level:                      Master thesis in Business Administration, 15 ECTS

    Institution:                School of Sustainable development of society and technology, Mälardalen University

    Authors:                  Abdulla Ahmed Ibrahim         Alexis Andersson

    Title:                       Aggregate complaints in MIS – A case study of Nordea Bank

    Tutor:                      Carl G Thunman

    Keywords:               Aggregate, complaint, dissatisfaction, content analysis, Nordea, MIS.

    Purpose:                  The paper aims to develop a model of how Nordea Bank can monitor customer dissatisfaction through aggregated dissatisfaction analysis. Furthermore, the study aims to identify improvement proposals in Nordea based on the developed model and conducted interviews.

    Method:                  This thesis consists of qualitative interviews. Personnel at the local office in Västerås has been interviewed as well as Nordea’s customer ombudsmen, former office employee at Nordea, data analyst, head of customer inquiries, Professor of database technology and also a researcher in language technology. A proprietary model was built based on the literature review constructed on variables that were expected to influence the monitoring process. The proprietary model was based on theory and formed the interview guide. The method that was used on the empirical data where “cut and paste”. The method was used to be able to place the interviews under each appropriate heading. The analysis then compared the empirical data with theories from the literature review, to be able to conduct a revised model and come up with a number of suggestions for improvement.

    Conclusion:            The model assumes wrongly that complaint and other grievances information can be integrated in the same process. There are several aggravating factors in Nordea's case; discontent information is in the current situation anonymous, it may be too small in scope for it to be profitable integrated or delivered in pre-packaged aggregate form. In this thesis, it became also clear that overall understanding should be based on a results-oriented attitude in which the results of the analysis provide employees with new insights to shape the monitoring process. Even at the central level, Nordea more often tends to follow up individual cases instead of analyzing them systematically in aggregate form, which the model does not take into account.

  • 320.
    Ahmed Ibrahim, Amina
    et al.
    Mälardalen University, School of Sustainable Development of Society and Technology.
    Basudde Nakajugo, Carol
    Mälardalen University, School of Sustainable Development of Society and Technology.
    Communities – en marknadsföringskanal med effekt?2008Independent thesis Basic level (degree of Bachelor), 10 points / 15 hpStudent thesis
    Abstract [en]

     

    Date:             2008-11-13

     

    Level:           Bachelor Thesis in Business Administration, 15 ECTS

     

    Authors:      Amina Ahmed Ibrahim               Carol Nakajugo Basudde

     

    Tutor:           Mats Viimne

     

    Title:             Communities – A marketing channel with effect?

     

    Purpose:       To describe communities as a marketing channel and its communication effect. 

     

    Method:       Primary data was collected through face-to-face, telephone and e-mail interviews. These interviews were used to gather information on the case studies used in this thesis. Four Swedish online communities namely Lunarstorm, Glife, Nightlife and Nattstad were used. Secondary data used in this thesis has consisted of books, articles and online sources.

     

    Conclusion:  Companies using communities as marketing channels have the added advantage of a higher segmentation which means that they can easier find and reach their target audience. One of the problems associated with this medium is that today many companies still suffer from a lack of knowledge when it comes to communities due to the fact that this medium has not been paid the attention that it needs. Companies prefer to rely more on the traditional marketing channels like TV, newspapers and radio. With this new found interest in communities and the attention being paid to them in the media, more and more companies are opening their eyes to these new marketing channels and are choosing to learn more about them.

     

  • 321.
    Ahmed Ibrahim, Amina
    et al.
    Mälardalen University, School of Sustainable Development of Society and Technology.
    Yola Konlaan, Beatrice
    Mälardalen University, School of Sustainable Development of Society and Technology.
    Nakajugo Basudde, Carol
    Mälardalen University, School of Sustainable Development of Society and Technology.
    Are competitors ready to take on a deregulated Apoteket AB?2008Independent thesis Advanced level (degree of Master (One Year)), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    Date: 2008-06-05

    Level: Master Thesis in Business Administration, 15 ECTS

    Authors: Amina Ahmed Ibrahim Beatrice Yola Konlaan Carol Nakajugo Basudde

    Tutor: Sigvard Herber

    Title: Are competitors ready to take on a deregulated Apoteket AB? Problem: With the oncoming deregulation of the monopoly, Apoteket AB appears to have a competitive advantage over incoming competition therefore the problem is to find out:

     What competitive advantage Apoteket AB has over its competitors.

     If the competitors have the tools to successfully compete with Apoteket AB.

    Purpose: The purpose of this thesis is to find out whether competitors in Sweden are able to compete successfully with Apoteket AB for the market of non prescription medicine.

    Method: Qualitative and quantitative methods have been used in this thesis. In order to achieve the desired result of this research it is appropriate to choose this approach since it enables the researcher to be able to explore all areas of the subject at hand and also give an in-depth discussion and analysis.

    Conclusion: Apoteket AB has several competitive advantages over its competitors. It has a strong brand name that is known and trusted by customers. While all three competing companies see themselves as complements to Apoteket AB, we think that the competitors have what it takes to successfully compete with Apoteket. Judging from previous cases such as Norway and Denmark which showed different outcomes of deregulation in the retail pharmaceutical industry, the competitors in both cases have not been on the losing side. Supermarkets, petrol stations and grocery stores in Denmark and Norway were also competing with their respective pharmacies based mainly on price, accessibility and convenience. In conclusion this is an indication that the competitors in Sweden have more than enough tools to successfully compete with Apoteket AB.

    Keywords: Deregulation, Pharmaceutical retail, Apoteket AB, Monopoly, Competition.

  • 322.
    Ahmed, Ismail
    et al.
    Mälardalen University, School of Business, Society and Engineering.
    Peksen, Ismail
    Mälardalen University, School of Business, Society and Engineering.
    Projektledarens färdväg mot kompetensutveckling: En analys av projektledarkompetens och planeringsverktyg hos JM AB2015Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    A project manager's responsibility in a project is to lead the project to specified goals with defined specifications. These goals must be achieved within a time related and economic framework. To achieve these goals, a project manager needs to early plan and implement a financial plan for the project. If the project manager lacks sufficient competence it may result in financial losses and failed project.  The present thesis was accomplished in collaboration with the construction company, JM AB, and the study consists of three parts. An extensive literature review has been conducted in which the theoretical perspective around the project have been analyzed. Interviews with project managers and site visits were conducted in order to achieve a deeper understanding of how JM works with timetables and existing competency development plans. The study shows that the project manager at JM AB is primarily involved in the early stages and the final stage of the project planning. Furthermore, this thesis showed that the project manager's skills development first of all takes place in daily work. In addition, the results showed that experience from previous work constitutes the most important skills development for the project managers and that activities such as formal courses also a contribute to stronger competence for the project manager.

  • 323.
    Ahmed, Mobyen Uddin
    Mälardalen University, School of Innovation, Design and Engineering.
    A case-based multi-modal clinical system for stress management2010Licentiate thesis, monograph (Other academic)
    Abstract [en]

    A difficult issue in stress management is to use biomedical sensor signal in the diagnosis and treatment of stress. Clinicians often make their diagnosis and decision based on manual inspection of physiological signals such as, ECG, heart rate, finger temperature etc. However, the complexity associated with manual analysis and interpretation of the signals makes it difficult even for experienced clinicians. Today the diagnosis and decision is largely dependent on how experienced the clinician is interpreting the measurements.  A computer-aided decision support system for diagnosis and treatment of stress would enable a more objective and consistent diagnosis and decisions.

    A challenge in the field of medicine is the accuracy of the system, it is essential that the clinician is able to judge the accuracy of the suggested solutions. Case-based reasoning systems for medical applications are increasingly multi-purpose and multi-modal, using a variety of different methods and techniques to meet the challenges of the medical domain. This research work covers the development of an intelligent clinical decision support system for diagnosis, classification and treatment in stress management. 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 have been investigated to enable a more reliable and efficient diagnosis and treatment of stress such as case-based reasoning, textual information retrieval, rule-based reasoning, and fuzzy logic. Functionalities and the performance of the system have been validated by implementing a research prototype based on close collaboration with an expert in stress. The case base of the implemented system has been initiated with 53 reference cases classified by an experienced clinician. A case study also shows that the system provides results close to a human expert. The experimental results suggest that such a system is valuable both for less experienced clinicians and for experts where the system may function as a second option.

  • 324.
    Ahmed, Mobyen Uddin
    Mälardalen University, School of Innovation, Design and Engineering.
    A Multimodal Approach for Clinical Diagnosis and Treatment2011Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    A computer-aided Clinical Decision Support System (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. Nevertheless, it has been a real challenge to design and develop such a functional system where accuracy of the system performance is an important issue.

    This research work focuses on development of intelligent CDSS based on a multimodal approach for diagnosis, classification and treatment in medical domains i.e. stress and post-operative pain management domains. Several Artificial Intelligence (AI) techniques such as Case-Based Reasoning (CBR), textual Information Retrieval (IR), Rule-Based Reasoning (RBR), Fuzzy Logic and clustering approaches have been investigated in this thesis work.

    Patient’s data i.e. their stress and pain related information are collected from complex data sources for instance, finger temperature measurements through sensor signals, pain measurements using a Numerical Visual Analogue Scale (NVAS), patient’s information from text and multiple choice questionnaires. The proposed approach considers multimedia data management to be able to use them in CDSSs for both the domains.

    The functionalities and performance of the systems have been evaluated based on close collaboration with experts and clinicians of the domains. In stress management, 68 measurements from 46 subjects and 1572 patients’ cases out of ≈4000 in post-operative pain have been used to design, develop and validate the systems. In the stress management domain, besides the 68 measurement cases, three trainees and one senior clinician also have been involved in order to conduct the experimental work. The result from the evaluation shows that the system reaches a level of performance close to the expert and better than the senior and trainee clinicians. Thus, the proposed CDSS could be used as an expert for a less experienced clinician (i.e. trainee) or as a second option/opinion for an experienced clinician (i.e. senior) to their decision making process in stress management. In post-operative pain treatment, the CDSS retrieves and presents most similar cases (e.g. both rare and regular) with their outcomes to assist physicians. Moreover, an automatic approach is presented in order to identify rare cases and 18% of cases from the whole cases library i.e. 276 out of 1572 are identified as rare cases by the approach. Again, among the rare cases (i.e. 276), around 57.25% of the cases are classified as ‘unusually bad’ i.e. the average pain outcome value is greater or equal to 5 on the NVAS scale 0 to 10. Identification of rear cases is an important part of the PAIN OUT project and can be used to improve the quality of individual pain treatment.

  • 325.
    Ahmed, Mobyen Uddin
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    A Personalized Health-Monitoring System for Elderly by Combining Rules and Case-based Reasoning2015In: Studies in Health Technology and Informatics, Volume 21: Proceedings of the 12th International Conference on Wearable Micro and Nano Technologies for Personalized Health, 2–4 June 2015, Västerås, Sweden, 2015, p. 249-254Conference paper (Refereed)
    Abstract [en]

    Health-monitoring system for elderly in home environment is a promising solution to provide efficient medical services that increasingly interest by the researchers within this area. It is often more challenging when the system is self-served and functioning as personalized provision. This paper proposed a personalized self-served health-monitoring system for elderly in home environment by combining general rules with a case-based reasoning approach. Here, the system generates feedback, recommendation and alarm in a personalized manner based on elderly’s medical information and health parameters such as blood pressure, blood glucose, weight, activity, pulse, etc. A set of general rules has used to classify individual health parameters. The case-based reasoning approach is used to combine all different health parameters, which generates an overall classification of health condition. According to the evaluation result considering 323 cases and k=2 i.e., top 2 most similar retrieved cases, the sensitivity, specificity and overall accuracy are achieved as 90%, 97% and 96% respectively. The preliminary result of the system is acceptable since the feedback; recommendation and alarm messages are personalized and differ from the general messages. Thus, this approach could be possibly adapted for other situations in personalized elderly monitoring.

  • 326.
    Ahmed, Mobyen Uddin
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    An Intelligent Healthcare Service to Monitor Vital Signs in Daily Life – A Case Study on Health-IoT2017In: International Journal of Engineering Research and Applications, ISSN 2248-9622, E-ISSN 2248-9622, Vol. 7, no 3, p. 43-55Article in journal (Refereed)
    Abstract [en]

    Vital signs monitoring for elderly in daily life environment is a promising concept that efficiently can provide medical services to people at home. However, make the system self-served and functioning as personalized provision makes the challenge even larger. This paper presents a case study on a Health-IoT system where an intelligent healthcare service is developed to monitor vital signs in daily life. Here, a generic Health-IoT framework with a Clinical Decision Support System (CDSS) is presented. The generic framework is mainly focused on the supporting sensors, communication media, secure and safe data communication, cloud-based storage, and remote accesses of the data. The CDSS is used to provide a personalized report on persons’ health condition based on daily basis observation on vital signs. Six participants, from Spain (n=3) and Slovenia (n=3) have been using the proposed healthcare system for eight weeks (e.g. 300+ health measurements) in their home environments to monitor their health. The sensitivity, specificity and overall accuracy of the DSS’s classification are achieved as 90%, 97% and 96% respectively while k=2 i.e., top 2 most similar retrieved cases are considered. The initial user evaluation result demonstrates the feasibility and performance of the implemented system through the proposed framework.

  • 327.
    Ahmed, Mobyen Uddin
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Altarabichi, Mohammed Ghaith
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Begum, Shahina
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Ginsberg, Fredrik
    Mälardalen University.
    Glaes, Robert
    Mälardalen University.
    Östgren, Magnus
    Mälardalen University.
    Rahman, Hamidur
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Sorensen, Magnus
    Mälardalen University.
    A vision-based indoor navigation system for individuals with visual impairment2019In: International Journal of Artificial Intelligence, ISSN 0974-0635, E-ISSN 0974-0635, Vol. 17, no 2, p. 188-201Article in journal (Refereed)
    Abstract [en]

    Navigation and orientation in an indoor environment are a challenging task for visually impaired people. This paper proposes a portable vision-based system to provide support for visually impaired persons in their daily activities. Here, machine learning algorithms are used for obstacle avoidance and object recognition. The system is intended to be used independently, easily and comfortably without taking human help. The system assists in obstacle avoidance using cameras and gives voice message feedback by using a pre-trained YOLO Neural Network for object recognition. In other parts of the system, a floor plane estimation algorithm is proposed for obstacle avoidance and fuzzy logic is used to prioritize the detected objects in a frame and generate alert to the user about possible risks. The system is implemented using the Robot Operating System (ROS) for communication on a Nvidia Jetson TX2 with a ZED stereo camera for depth calculations and headphones for user feedback, with the capability to accommodate different setup of hardware components. The parts of the system give varying results when evaluated and thus in future a large-scale evaluation is needed to implement the system and get it as a commercialized product in this area.

  • 328.
    Ahmed, Mobyen Uddin
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Andersson, Peter
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Andersson, Tim
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Tomas Aparicio, Elena
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center. Malardalen Univ, Future Energy Ctr, Sch Business Soc & Engn, SE-72123 Vasteras, Sweden.;Malarenergi AB, Sjohagsvagen 3, S-72103 Vasteras, Sweden..
    Baaz, Hampus
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Barua, Shaibal
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Bergström, Albert
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Bengtsson, Daniel
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Orisio, Daniele
    State Inst Higher Educ Guglielmo Marconi, Dalmine, Italy..
    Skvaril, Jan
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Zambrano, Jesus
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    A Machine Learning Approach for Biomass Characterization2019In: INNOVATIVE SOLUTIONS FOR ENERGY TRANSITIONS / [ed] Yan, J Yang, HX Li, H Chen, X, ELSEVIER SCIENCE BV , 2019, p. 1279-1287Conference paper (Refereed)
    Abstract [en]

    The aim of this work is to apply and evaluate different chemometric approaches employing several machine learning techniques in order to characterize the moisture content in biomass from data obtained by Near Infrared (NIR) spectroscopy. The approaches include three main parts: a) data pre-processing, b) wavelength selection and c) development of a regression model enabling moisture content measurement. Standard Normal Variate (SNV), Multiplicative Scatter Correction and Savitzky-Golay first (SGi) and second (SG2) derivatives and its combinations were applied for data pre-processing. Genetic algorithm (GA) and iterative PLS (iPLS) were used for wavelength selection. Artificial Neural Network (ANN), Gaussian Process Regression (GPR), Support Vector Regression (SVR) and traditional Partial Least Squares (PLS) regression, were employed as machine learning regression methods. Results shows that SNV combined with SG1 first derivative performs the best in data pre-processing. The GA is the most effective methods for variable selection and GPR achieved a high accuracy in regression modeling while having low demands on computation time. Overall, the machine learning techniques demonstrate a great potential to be used in future NIR spectroscopy applications.

  • 329.
    Ahmed, Mobyen Uddin
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Andersson, Peter
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Andersson, Tim
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Tomas Aparicio, Elena
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center. Mälarenergi AB, Sweden.
    Baaz, Hampus
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Barua, Shaibal
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems. RISE SICS, Sweden.
    Bergström, Albert
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Bengtsson, Daniel
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Skvaril, Jan
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Zambrano, Jesus
    Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
    Real-time Biomass Characterization in Energy Conversion Processes using Near Infrared Spectroscopy: A Machine Learning Approach2019In: “Innovative Solutions for Energy Transitions” / [ed] Elsevier, 2019, Vol. 158, p. 1279-1287Conference paper (Refereed)
    Abstract [en]

    The aim of this work is to apply and evaluate different chemometric approaches employing several machine learning techniques in order to characterize the moisture content in biomass from data obtained by Near Infrared (NIR) spectroscopy. The approaches include three main parts: a) data pre-processing, b) wavelength selection and c) development of a regression model enabling moisture content measurement. Standard Normal Variate (SNV), Multiplicative Scatter Correction and Savitzky-Golay first (SG1) and second (SG2) derivatives and its combinations were applied for data pre-processing. Genetic algorithm (GA) and iterative PLS (iPLS) were used for wavelength selection. Artificial Neural Network (ANN), Gaussian Process Regression (GPR), Support Vector Regression (SVR) and traditional Partial Least Squares (PLS) regression, were employed as machine learning regression methods. Results shows that SNV combined with SG1 first derivative performs the best in data pre-processing. The GA is the most effective methods for variable selection and GPR achieved a high accuracy in regression modeling while having low demands on computation time. Overall, the machine learning techniques demonstrate a great potential to be used in future NIR spectroscopy applications.

  • 330.
    Ahmed, Mobyen Uddin
    et al.
    Örebro University, Sweden.
    Banaee, Hadi
    Örebro University, Sweden.
    Loutfi, Amy
    Örebro University, Sweden.
    Health Monitoring for Elderly: An Application Using Case-Based Reasoning and Cluster Analysis2013In: ISRN Artificial Intelligence, ISSN 2090-7435, E-ISSN 2090-7443, ISRN Artificial Intelligence ISRNAI, ISSN 2356-7872, p. rticle ID 380239-Article in journal (Refereed)
    Abstract [en]

    This paper presents a framework to process and analyze data from a pulse oximeter which remotely measures pulse rate and blood oxygen saturation from a set of individuals. Using case-based reasoning (CBR) as the backbone to the framework, records are analyzed and categorized according to their similarity. Record collection has been performed using a personalized health profiling approach in which participants wore a pulse oximeter sensor for a fixed period of time and performed specific activities for pre-determined intervals. Using a variety of feature extraction methods in time, frequency, and time-frequency domains, as well as data processing techniques, the data is fed into a CBR system which retrieves most similar cases and generates an alarm according to the case outcomes. The system has been compared with an expert's classification, and a 90% match is achieved between the expert's and CBR classification. Again, considering the clustered measurements, the CBR approach classifies 93% correctly both for the pulse rate and oxygen saturation. Along with the proposed methodology, this paper provides a basis for which the system can be used in the analysis of continuous health monitoring and can be used as a suitable method in home/remote monitoring systems.

  • 331.
    Ahmed, Mobyen Uddin
    et al.
    Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.
    Banaee, Hadi
    Loutfi, Amy
    Rafael-Palou, Xavier
    Intelligent Healthcare Services to Support Health Monitoring of Elderly2014In: International Conference on IoT Technologies for HealthCare HealthyIoT, Rome, Italy, 2014Conference paper (Refereed)
    Abstract [en]

    This paper proposed an approach of intelligent healthcare services to support health monitoring of old people through the project named SAAPHO. Here, definition and architecture of the proposed healthcare services are presented considering six different health parameters such as: 1) physical activity, 2) blood pressure, 3) glucose, 4) medication compliance, 5) pulse monitoring and 6) weight monitoring. The outcome of the proposed services is evaluated in a case study where total 201 subjects from Spain and Slovenia are involved for user requirements analysis considering 1) end users, 2) clinicians, and 3) field study analysis perspectives. The result shows the potentiality and competence of the proposed healthcare services for the users.

  • 332.
    Ahmed, Mobyen Uddin
    et al.
    Mälardalen University, School of Innovation, Design and Engineering.
    Begum, Shahina
    Mälardalen University, School of Innovation, Design and Engineering.
    Bibliometric Profiling of a Group: A Discussion on Different Indicators2011Report (Other academic)
    Abstract [en]

    Now-a-days in some advanced countries bibliometric profiling plays a vital role when making decision on promotion, fund allocation and award prizes. Accurate identification of this is important since it is becoming important to assess scientific output for a researcher or a group of researcher. This paper presents and discusses several most common indicators of bibliometric profiling together with h- and g-indexes. A case study has been conducted on 101 scientific articles with three most well known search engines. The study results using several indicators are presented in this report.

  • 333.
    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. IS (Embedded Systems).
    Big Data Analytics in Health Monitoring at Home2017In: Medicinteknikdagarna 2017 MTD 2017, 2017Conference paper (Refereed)
    Abstract [en]

    This paper proposed a big data analytics approach applied in the projects ESS-H and E-care@home in the context of biomedical and health informatics with the advancement of information fusion, data abstraction, data mining, knowledge discovery, learning, and reasoning [1][2]. Data are collected through the projects, considering both the health parameters, e.g. temperature, bio-impedance, skin conductance, heart sound, blood pressure, pulse, respiration, weight, BMI, BFP, movement, activity, oxygen saturation, blood glucose, heart rate, medication compliance, ECG, EMG, and EEG, and the environmental parameters e.g. force/pressure, infrared (IR), light/luminosity, photoelectric, room-temperature, room-humidity, electrical usage, water usage, RFID localization and accelerometers. They are collected as semi-structured/unstructured, continuous/periodic, digital/paper record, single/multiple patients, once/several-times, etc. and stored in a central could server [5]. Thus, with the help of embedded system, digital technologies, wireless communication, Internet of Things (IoT) and smart sensors, massive quantities of data (so called ‘Big Data’) with value, volume, velocity, variety, veracity and variability are achieved [2]. The data analysis work in the following three steps. In Step1, pre-processing, future extraction and selection are performed based on a combination of statistical, machine learning and signal processing techniques. A novel strategy to fuse the data at feature level and as well as at data level considers a defined fusion mechanism [3]. In Step2, a combination of potential sequences in the learning and search procedure is investigated. Data mining and knowledge discovery, using the refined data from the above for rule extraction and knowledge mining, with support for anomaly detection, pattern recognition and regression are also explored here [4]. In Step3, adaptation of knowledge representation approaches is achieved by combining different artificial intelligence methods [3] [4]. To provide decision support a hybrid approach is applied utilizing different machine learning algorithms, e.g. case-based reasoning, and clustering [4]. The approach offers several data analytics tasks, e.g. information fusion, anomaly detection, rules and knowledge extraction, clustering, pattern identification, correlation analysis, linear regression, logic regression, decision trees, etc. Thus, the approach assist in decision support, early detection of symptoms, context awareness and patient’s health status in a personal environment.

  • 334.
    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.
    Catalina, Carlos Alberto
    ITCL Polígono Industrial Villalonquéjar c/López Bravo, 70. 09001 BURGOS, Spain.
    Limonad, Lior
    Smart Wearable and IoT Solutions, IBM Research, Haifa, Israil.
    Hök, Bertil
    Hök Instrument AB, Sweden.
    Flumeri, Gianluca Di
    Cognitive States in Operative Environment, BrainSigns, Italy.
    Cloud-based Data Analytics on Human Factor Measurement to Improve Safer Transport2018In: Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST, Volume 225, 2018, p. 101-106Conference paper (Refereed)
    Abstract [en]

    Improving safer transport includes individual and collective behavioural aspects and their interaction. A system that can monitor and evaluate the human cognitive and physical capacities based on human factor measurement is often beneficial to improve safety in driving condition. However, analysis and evaluation of human factor measurement i.e. Demographics, Behavioural and Physiological in real-time is challenging. This paper presents a methodology for cloud-based data analysis, categorization and metrics correlation in real-time through a H2020 project called SimuSafe. Initial implementation of this methodology shows a step-by-step approach which can handle huge amount of data with variation and verity in the cloud.

  • 335.
    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.
    A Hybrid Case-Based System in Stress Diagnosis and Treatment2012Manuscript (preprint) (Other academic)
    Abstract [en]

    Computer-aided decision support systems play anincreasingly important role in clinical diagnosis and treatment.However, they are difficult to build for domains where thedomain theory is weak and where different experts differ indiagnosis. Stress diagnosis and treatment is an example of such adomain. This paper explores several artificial intelligencemethods and techniques and in particular case-based reasoning,textual information retrieval, rule-based reasoning, and fuzzylogic to enable a more reliable diagnosis and treatment of stress.The proposed hybrid case-based approach has been validated byimplementing a prototype in close collaboration with leadingexperts in stress diagnosis. The obtained sensitivity, specificityand overall accuracy compared to an expert are 92%, 86% and88% respectively.

  • 336.
    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.
    A Multi-Modal Case-Based System for Clinical Diagnosis and Treatment in Stress Management2009In: / [ed] Delany, S.J., 2009, p. 215-224Conference paper (Refereed)
    Abstract [en]

    A difficult issue in stress management is to use biomedical sensor signal in the diagnosis and treatment of stress. Clinicians often base their diagnosis and decision on manual inspection of signals such as, ECG, heart rate, finger temperature etc. However, the complexity associated with the manual analysis and interpretation of the signals makes it difficult even for experienced clinicians. A computer system, classifying the sensor signals is one valuable property assisting a clinician. This paper presents a case-based system that assist 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, 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 the experts. The experimental results suggest that such a system is valuable both for the less experienced clinicians and for experts where the system may be seen as a second option.

  • 337.
    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.

  • 338.
    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.

  • 339.
    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.

  • 340.
    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.

  • 341.
    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.

  • 342.
    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. 

  • 343.
    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.

  • 344.
    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.

  • 345.
    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.

  • 346.
    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.

  • 347.
    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.

  • 348.
    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.

  • 349.
    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.

  • 350.
    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.

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