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  • 1.
    Askfors, Ylva
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Health Informatics.
    Samverkan för innovation: En fallstudie av mötet mellan akademi, industri och sjukvård2018Doctoral thesis, monograph (Other academic)
    Abstract [sv]

    Samverkan kan leda till innovation, konkurrenskraftiga företag, förstklassig forskning samt välfungerande myndigheter och institutioner. I den politiska debatten idag finns en förväntan att Sverige ska upprätthålla sin konkurrenskraft och bemöta samhällets utmaningar genom innovation och att vägen till innovation går via samverkan. Avhandlingen bygger på en studie av ett samverkansprojekt vars syfte var att skapa innovation för att minska antalet vårdrelaterade infektioner i Sverige. Projektet som studerats ses som en transdisciplinär ansats med aktörer som representerade akademi, industri samt hälso- och sjukvård.

    Syftet med avhandlingen är att vidareutveckla kunskapen om interorganisatorisk samverkan för innovation. Detta görs genom ett tredelat bidrag, till teoribildningen kring samverkan för innovation som börjat växa fram, till den samverkande praktiken inom både privat och offentlig sektor samt till politiker och beslutsfattare som styr fördelning av statliga anslag till forskning och innovation.

    Fallstudien som ligger till grund för avhandlingen är baserad på en etnografiskt inspirerad studie. Empiriskt material samlades in och skapades tillsammans med aktörerna i projektet under drygt två års tid genom intervjuer och deltagande observation.

    Studien visar att interorganisatorisk samverkan består av flera dimensioner och kan förstås på flera nivåer. Interorganisatorisk samverkan innebär inte bara att det är olika organisationer som ska göra en gemensam ansträngning. Organisationerna består av olika människor med olika discipliner och professioner vilka bygger på olika utgångspunkter och sätt att se på världen. Samverkan kan ses som ett sätt att fylla mellanrummen mellan organisationer istället för att bygga broar över gränser. I de organisatoriska mellanrummen kan aktörer från olika organisationer, med olika discipliner och professioner mötas utan institutionaliserade roller, i en receptiv kontext där innovation kan skapas.

  • 2.
    Askfors, Ylva
    et al.
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Health Informatics.
    Fornstedt, Helena
    Uppsala universitet.
    The clash of managerial and professional logics in public procurement: Implications for innovation in the health-care sector.2018In: Scandinavian Journal of Management, ISSN 0956-5221, E-ISSN 1873-3387, Vol. 34, no 1, p. 78-90Article in journal (Refereed)
    Abstract [en]

    This article addresses the enactment of public procurement and its influence on adoption and diffusion of innovation, using a case study of public procurement of a low-tech medical device innovation in Swedish healthcare. Based on interviews and documentation, the article illustrates the various perspectives of the different professions involved in the complex task of setting the requirement specification for the tender. The technology identities of the medical device (innovation) are constructed and negotiated by the actors: procurement administrators, health-care professionals and suppliers within the adoption space. Examining the enactment of the procurement process as part of the adoption space is a way to deepen our understanding of the social component within public procurement.

  • 3.
    Beijner, David
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Health Informatics.
    Ökad lokal nytta av förnyelsebar energiproduktion med hybridkraftverk2018Independent thesis Basic level (university diploma), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    Renewable and environmentally friendly electricity production is a necessity for the relative positive value of the products and processes that consumes electricity. It is not enough that these products and processes in and of themselves are effective in their use of electricity if that electricity is produced with non- renewable means. The goal of this project is the creation of a simulation software that can simulate a hybrid powerplant composed of wind turbines and a hydro powerplant. The result of this project is a simulation software that is able is to approximate the size of a pumped-storage megawatts and the size of the reservoir needed. In addition, the software calculates the amount of wind turbines needed in combination with the hydro powerplant to achieve a desired decrease in non-renewable electricity.

  • 4.
    Ejdemark, Johan
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Health Informatics.
    Automatisk detektering av andning2018Independent thesis Basic level (university diploma), 10 credits / 15 HE creditsStudent thesis
    Abstract [sv]

    Hammed Hammid Mohammed, universitetsadjunkt vid KTH i Flemingsberg gav uppdragetatt utveckla en mobil kontaktlös andningsbevakare för spädbarn och äldre i form av en mobilapplikationsom använder sig av kameran för att detektera fel i andningen. Denna skullefungera som ett billigare och enklare alternativ till konventionella andningsbevakningsinstrument.Uppgiften utfördes genom att först genomföra en litteraturstudie för att finna olikaalgoritmer och matematiska modeller att implementera och testa. Andra steget var att testade mest lämpade algoritmerna och matematiska modellerna i en datorprototyp gjord i Matlabför att se ifall dessa fungerade som det var tänkt. Tredje steget var att föra över datorprototypensalgoritmer så fullständigt som möjligt till en mobilapplikation.Arbetet resulterade i en algoritm, implementerbar i mobiltelefon, som kan ingå som indikationpå att andning pågår. Detta föregicks av tester av olika parametrar såsom belysning, kontraster,avstånd, position och vinklar mellan mobilkameran och försökspersonen. Testernavisade att stark ljussättning, goda kontraster mellan försöksperson och bakgrund samt rättavstånd och position mellan kamera och försöksperson gav goda resultat.Resultatet i sin helhet gav insikten att användandet av den matematiska algoritmen FFT (FastFourier Transform) kan ingå som indikator på att det är andning som detekteras.

  • 5.
    Ekenstedt, Christian
    et al.
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Health Informatics.
    Holmström, Gustaf
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Health Informatics.
    Artificiell intelligens och maskinlärning i finansbranschen2018Independent thesis Basic level (university diploma), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    To always be able to offer their services as a financial institution, it’s important for them to always stay informed and updated when new regulations come into force. Today it contributes to high costs, largely due to humanitarian power. A literature study was performed to see as to what extent artificial intelligence or machine learning could be used to reduce the problem. The result of the study showed that machine learning was the best suited method for this problem. There were not the most optimal conditions to achieve the best possible result, despite that, the result gave promising ability to classify products to regulations. The possibility of applying machine learning and artificial intelligence is good but it is important to have extremely large amounts of training and test data in order to make the financial industry more effective. 

  • 6.
    Galdo, Carlos
    et al.
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Health Informatics.
    Chavez, Teddy
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Health Informatics.
    Prototyputveckling för skalbar motor med förståelse för naturligt språk2018Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    Natural Language Understanding is a field that is part of Natural Language Processing. Big improvements have been made in the broad field of Natural Language Understanding during the past two decades. One big contribution to this is improvement is Neural Networks, a mathematical model inspired by biological brains. Natural Language Understanding is used in fields that require deeper understanding by applications. Google translate, Google search engine and grammar/spelling check are some examples of applications requiring deeper understanding.

    Thing Launcher is an application developed by A Great Thing AB. Thing Launcher is an application capable of managing other applications with different parameters. Some examples of parameters the user can use are geographic position and time. The user can as an example control what song will be played when you get home or order an Uber when you arrive to a certain destination. It is possible to control Thing Launcher today by text input. A Great Thing AB needs help developing a prototype capable of understanding text input and speech. The meaning of scalable is that it should be possible to develop, add functions and applications with as little impact as possible on up time and performance of the service. A comparison of suitable algorithms, tools and frameworks has been made in this thesis in order research what it takes to develop a scalable engine with the natural language understanding and then build a prototype from this gathered information. A theoretical comparison was made between Hidden Markov Models and Neural Networks. The results showed that Neural Networks are superior in the field of natural language understanding. The tests made in this thesis indicated that high accuracy could be achieved using neural networks. TensorFlow framework was chosen because it has many different types of neural network implemented in C/C++ ready to be used with Python and alsoand for the wide compatibility with mobile devices.  The prototype should be able to identify voice commands. The prototype has two important components called Command tagger, which is going to identify which application the user wants to control and NER tagger, which is the going to identify what the user wants to do. To calculate the accuracy, two types of tests, one for each component, was executed several times to calculate how often the components guessed right after each training iteration. Each training iteration consisted of giving the components thousands of sentences to guess and giving them feedback by then letting them know the right answers. With the help of feedback, the components were molded to act right in situations like the training. The tests after the training process resulted with the Command tagger guessing right 94% of the time and the NER tagger guessing right 96% of the time.

    The built-in software in Android was used for speech recognition. This is a function that converts sound waves to text. A server-based solution with REST interface was developed to make the engine scalability.

    This thesis resulted with a working prototype that can be used to further developed into a scalable engine.

  • 7.
    Gyllencreutz, E.
    et al.
    Karolinska Inst, Stockholm, Sweden.;Ostersund Hosp, Dept Obstet & Gynecol, Ostersund, Sweden..
    Lu, Ke
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Health Informatics.
    Lindecrantz, Kaj
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Health Informatics. Karolinska Inst, Stockholm, Sweden.
    Lindqvist, P.
    Karolinska Inst, Stockholm, Sweden..
    Nordström, L.
    Karolinska Inst, Stockholm, Sweden..
    Holzmann, M.
    Karolinska Inst, Stockholm, Sweden.;Karolinska Univ Hosp, Dept Obstet & Gynecol, Stockholm, Sweden..
    Abtahi, F.
    Karolinska Inst, Stockholm, Sweden.;Karolinska Univ Hosp, Dept Clin Physiol, Stockholm, Sweden..
    Validation of a computerised algorithm to quantify fetal heart rate deceleration area: An observational study2018In: British Journal of Obstetrics and Gynecology, ISSN 1470-0328, E-ISSN 1471-0528, Vol. 125, p. 54-54Article in journal (Other academic)
  • 8.
    Kamras, Ludwig
    et al.
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Health Informatics.
    Matslova, William
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Health Informatics.
    An approach to a Multi-Category Recommendation System using Machine Learning: With the caveat of having limited knowledge in related areas2018Independent thesis Basic level (university diploma), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    Machine learning is one of many buzz words in todays tech-world. Huge company resources are allocated to the field in order to discover its potential. Everything from cameras to cars tries to use this technology. However, the question is if developers with little experience in the field can use this technology in a useful way? And how would one proceed with that? This thesis tries to answer these questions by having two third year undergraduate students attempt to implement a multi-category movie recommendation system using machine learning. With the important caveat of neither student having any previous knowledge in machine learning, recommendation systems nor the chosen programming language (Python).

    An extensive background study was performed in order to obtain knowledge in the different areas. Recommendation systems often use either collaborative, or content-based filtering, or a hybrid of the two. Machine learning uses different algorithms, a selection of these where studied together with available frameworks.

    In order to implement and design a system, a data-set from MovieLens, containing ratings of movies, and the framework SciKit-learn was used. The implementation tried to use genres in order to give movie recommendations. This was done in two systems, one where every user got a genre-weight and the other system used Nearest Neighbor in order to use the collaborative filtering approach. However, due to the limited time the implementation was not implemented for multiple categories, but the results showed that this should be highly applicable using the proposed design.

    The thesis showed that even two third year undergraduate students with no prior knowledge in the areas could make use of machine learning in an system implementation. The results of the project was presented in two different parts; Firstly, the system implementation result showed that the accuracy metric was not at a satisfactory level. Even though the concept of using genres as a metric for giving recommendations worked, it was seemingly to simple and broad. Secondly, the project result showed that the majority of the time was spent on the preliminary work and the system implementation. Finally the economical cost of the project was presented.

  • 9.
    Karbalaie, Abdolamir
    et al.
    KTH, School of Technology and Health (STH).
    Fatemi, Alimohammad
    Department of Rheumatology, Alzahra Hospital, Isfahan University of Medical Sciences.
    Etehadtavakol, Mahnaz
    Medical Image and Signal Processing Research Center, Isfahan University of Medical Sciences.
    Abtahi, Farhad
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Health Informatics. Department of Clinical Science, Intervention and Technology, Karolinska Institute (KI).
    Emrani, Zahra
    Medical Image and Signal Processing Research Center, Isfahan University of Medical Sciences.
    Erlandsson, Björn-Erik
    KTH, School of Technology and Health (STH), Health Systems Engineering, Systems Safety and Management.
    Counting Capillaries in Nailfold Capillaroscopy:State of the Art and a Proposed Method2016In: 2016 IEEE EMBS CONFERENCE ON BIOMEDICAL ENGINEERING AND SCIENCES (IECBES), IEEE, 2016, , p. 5p. 170-174Conference paper (Refereed)
    Abstract [en]

    Capillaries play a crucial role in the microcirculatory system by exchanging metabolic substrates and waste products between blood and various tissues. The behavior of capillaries is affiliated with the number of capillaries per unit volume of tissue. Among the various noninvasive techniques available for analyzing skin microcirculation, nailfold capillaroscopyis considered to be a simple and easy-to-perform technique that allows a direct in-vivo visualization of the capillary network.Capillary density is one of the most important parameters in the studies involving capillaroscopy images. Capillary density in most of studies is defined as the number of capillaries in a one-millimeter span of the distal row in each finger or toe. This definition is silent about counting or excluding the number of the capillary with different shapes. However, there is no single standard for counting the number of capillaries in a span of one millimeter. In this paper, a novel method is proposed for determining the nailfold capillary density. This method is a modified combination of two existing techniques: the direct observation and the 90◦ method.Compared to the two existing approaches, the proposed method is more straightforward and easy to use for cases in which the capillaries have different shapes and sizes. Through different examples, we have shown how this method can be used to select the apex point of the capillary and subsequently count the number of capillaries with several papillae.

  • 10.
    Lu, Ke
    et al.
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Health Informatics. Royal Inst Technol, Stockholm, Sweden..
    Holzmann, M.
    Karolinska Inst, Stockholm, Sweden.;Karolinska Univ Hosp, Dept Obstet & Gynecol, Stockholm, Sweden..
    Abtahi, F.
    Karolinska Inst, Stockholm, Sweden.;Karolinska Univ Hosp, Dept Clin Physiol, Stockholm, Sweden..
    Lindecrantz, Kaj
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Health Informatics. Karolinska Univ Hosp, Dept Clintec, Stockholm, Sweden..
    Lindqvist, P.
    Karolinska Inst, Stockholm, Sweden.;Karolinska Univ Hosp, Dept Clintec, Stockholm, Sweden..
    Nordström, L.
    Karolinska Inst, Stockholm, Sweden..
    Fetal heart rate short term variation (STV) during labour in relation to early stages of hypoxia: An observational study2018In: British Journal of Obstetrics and Gynecology, ISSN 1470-0328, E-ISSN 1471-0528, Vol. 125, p. 55-55Article in journal (Other academic)
  • 11.
    Mossberg, Ivar
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Health Informatics.
    Dimensionering av dvärgbrytare för kraft- och spänningsmatningar på Forsmarks Kraftgrupp AB: Beräkningsmetodik och anvisning för dimensionering av dvärgbrytare.2018Independent thesis Basic level (university diploma), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    This thesis is performed on behalf of the department of Systemkonstruktion El at Forsmarks Kraftgrupp AB.This report deals with the task of making an inventory for miniature circuit break-ers (MCB). The aim of the graduation work is to design a quick reference so that the choice of cable and in some cases even MCB’s can be performed by the designer in connection with electrical design. This involves reporting a calculation method for selecting MCB’s in different applications. MCB’s in both AC voltage and DC voltage systems are affected.As reference for Forsmark, this report deals with the system 519.The problem lies in in delimiting the work since every reactor at Forsmark consists of approximately 4000 MCB’s of different characteristics and applications. A very huge importance is also given to parameters specified in SS-EN standards for load capacity.The thesis began with a pilot study of the pros and cons of MBC’s in different appli-cations, which rules control the dimensioning and how the design is carried out today, etc. An analysis was performed based on formulas and calculations present-ed in Swedish Standard such as SS 424 14 03, resulted in a quick reference.

  • 12. Naweed, A.
    et al.
    Wardaszko, M.
    Leigh, E.
    Meijer, Sebastiaan
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Health Informatics.
    Preface2018In: 21st Annual Simulation Technology and Training Conference, SimTecT 2016 and 47th International Simulation and Gaming Association Conference, ISAGA 2016 Held as Part of the 1st Australasian Simulation Congress, ASC 2016, Springer Verlag , 2018, p. v-viConference paper (Refereed)
  • 13.
    Scott, Robert
    et al.
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Health Informatics.
    Östberg, Daniel
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Health Informatics.
    A comparative study of open-source IoT middleware platforms.2018Independent thesis Basic level (university diploma), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    This is a comparative study of open-source IoT middleware platforms with the main focus on scalability and reliability. An initial evaluation of available open-source IoT platforms resulted in Kaa and Node-RED being the focus of this thesis. To further analyse the platforms, they were both subjected to testing with three real-world scenarios. The chosen scenarios were a remote-controlled LED, a chat application and a data transmitting sensor. Prototypes were developed for each scenario using a range of programming languages and devices like Raspberry Pi, Android and ESP8266.According to the tests Node-RED has better performance on a single server. It also scales better with the possibility to communicate with external APIs directly unlike Kaa which would require a gateway. Despite these factors, Kaa proved to have better overall scalability and reliability with its built-insecurity and device discovery, it also supports clustering and should prove better in larger environments.

  • 14.
    Söder, Jenny
    et al.
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Health Informatics.
    Palmqvist, Markus
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Health Informatics.
    Prediktion av sannolikhet med maskininlärning och pris för sårbarheter i programvaruprodukter: Prototyper med algoritmer för prediktion av sårbarheter2018Independent thesis Basic level (university diploma), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    The project explores the possibilities of predicting software product vulnerabilities and the type of vulnerability that will be found. It is an indication of how vulnerable a system is on how often a vulnerability is found. Machine learning is a way to read patterns from a large amount of data and can help with prioritization. With publicly available data on vulnerabilities, machine learning has been used to find a method of making predictions about the number of future vulnerabilities.

    prototypes have been developed and reviewed for which prototype that performs

    best. An analysis of the results shows that the content of the data should be evenly

    divided between classes in such type of survey to get a good and reliable result.

    The number of public vulnerabilities found and published has increased in recent

    years and appears to continue in the same trend. An analysis of how the market and

    selling price are looking for vulnerabilities shows that the global economy is growing

    rapidly and the turnover for machine learning will increase significantly as it

    recognizes its benefits to more areas.

1 - 14 of 14
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