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  • 1.
    Aasberg Pipirs, Freddy
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS).
    Svensson, Patrik
    KTH, School of Electrical Engineering and Computer Science (EECS).
    Tenancy Model Selection Guidelines2018Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    Software as a Service (SaaS) is a subset of cloud services where a vendor provides software as a service to customers. The SaaS application is installed on the SaaS provider’s servers, and is often accessed via the web browser. In the context of SaaS, a customer is called tenant, which often is an organization that is accessing the SaaS application, but it could also be a single individual. A SaaS application can be classified into tenancy models. A tenancy model describes how a tenant’s data is mapped to the storage on the server-side of the SaaS application.By doing a research, the authors have drawn the conclusion that there is a lack of guidance for selecting tenancy models. The purpose of this thesis is to provide guidance for selecting tenancy models. The short-term-goal is to create a tenancy selection guide. The long-term-goal is to provide researchers and students with research material. This thesis provides a guidance model for selection of tenancy models. The model is called Tenancy Model Selection Guidelines (TMSG).TMSG was evaluated by interviewing two professionals from the software industry. The criteria used for evaluating TMSG were Interviewee credibility, Syntactic correctness, Semantic correctness, Usefulness and Model flexibility. In the interviews, both of the interviewees said that TMSG was in need of further refinements. Still they were positive to the achieved result.

  • 2.
    Abbas, Zainab
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Software and Computer systems, SCS.
    Al-Shishtawy, Ahmad
    RISE SICS, Stockholm, Sweden.
    Girdzijauskas, Sarunas
    KTH, School of Electrical Engineering and Computer Science (EECS), Software and Computer systems, SCS. RISE SICS, Stockholm, Sweden..
    Vlassov, Vladimir
    KTH, School of Electrical Engineering and Computer Science (EECS), Software and Computer systems, SCS.
    Short-Term Traffic Prediction Using Long Short-Term Memory Neural Networks2018Conference paper (Refereed)
    Abstract [en]

    Short-term traffic prediction allows Intelligent Transport Systems to proactively respond to events before they happen. With the rapid increase in the amount, quality, and detail of traffic data, new techniques are required that can exploit the information in the data in order to provide better results while being able to scale and cope with increasing amounts of data and growing cities. We propose and compare three models for short-term road traffic density prediction based on Long Short-Term Memory (LSTM) neural networks. We have trained the models using real traffic data collected by Motorway Control System in Stockholm that monitors highways and collects flow and speed data per lane every minute from radar sensors. In order to deal with the challenge of scale and to improve prediction accuracy, we propose to partition the road network into road stretches and junctions, and to model each of the partitions with one or more LSTM neural networks. Our evaluation results show that partitioning of roads improves the prediction accuracy by reducing the root mean square error by the factor of 5. We show that we can reduce the complexity of LSTM network by limiting the number of input sensors, on average to 35% of the original number, without compromising the prediction accuracy.

  • 3.
    Abbas, Zainab
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Software and Computer systems, SCS.
    Kalavri, Vasiliki
    Systems Group, ETH, Zurich, Switzerland.
    Carbone, Paris
    KTH, School of Electrical Engineering and Computer Science (EECS), Software and Computer systems, SCS.
    Vlassov, Vladimir
    KTH, School of Electrical Engineering and Computer Science (EECS), Software and Computer systems, SCS.
    Streaming Graph Partitioning: An Experimental Study2018In: Proceedings of the VLDB Endowment, ISSN 2150-8097, E-ISSN 2150-8097, Vol. 11, no 11, p. 1590-1603Article in journal (Refereed)
    Abstract [en]

    Graph partitioning is an essential yet challenging task for massive graph analysis in distributed computing. Common graph partitioning methods scan the complete graph to obtain structural characteristics offline, before partitioning. However, the emerging need for low-latency, continuous graph analysis led to the development of online partitioning methods. Online methods ingest edges or vertices as a stream, making partitioning decisions on the fly based on partial knowledge of the graph. Prior studies have compared offline graph partitioning techniques across different systems. Yet, little effort has been put into investigating the characteristics of online graph partitioning strategies.

    In this work, we describe and categorize online graph partitioning techniques based on their assumptions, objectives and costs. Furthermore, we employ an experimental comparison across different applications and datasets, using a unified distributed runtime based on Apache Flink. Our experimental results showcase that model-dependent online partitioning techniques such as low-cut algorithms offer better performance for communication-intensive applications such as bulk synchronous iterative algorithms, albeit higher partitioning costs. Otherwise, model-agnostic techniques trade off data locality for lower partitioning costs and balanced workloads which is beneficial when executing data-parallel single-pass graph algorithms.

  • 4.
    Abbas, Zainab
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Software and Computer systems, SCS.
    Sigurdsson, Thorsteinn Thorri
    KTH.
    Al-Shishtawy, Ahmad
    RISE Res Inst Sweden, Stockholm, Sweden..
    Vlassov, Vladimir
    KTH, School of Electrical Engineering and Computer Science (EECS), Software and Computer systems, SCS.
    Evaluation of the Use of Streaming Graph Processing Algorithms for Road Congestion Detection2018In: 2018 IEEE INT CONF ON PARALLEL & DISTRIBUTED PROCESSING WITH APPLICATIONS, UBIQUITOUS COMPUTING & COMMUNICATIONS, BIG DATA & CLOUD COMPUTING, SOCIAL COMPUTING & NETWORKING, SUSTAINABLE COMPUTING & COMMUNICATIONS / [ed] Chen, JJ Yang, LT, IEEE COMPUTER SOC , 2018, p. 1017-1025Conference paper (Refereed)
    Abstract [en]

    Real-time road congestion detection allows improving traffic safety and route planning. In this work, we propose to use streaming graph processing algorithms for road congestion detection and evaluate their accuracy and performance. We represent road infrastructure sensors in the form of a directed weighted graph and adapt the Connected Components algorithm and some existing graph processing algorithms, originally used for community detection in social network graphs, for the task of road congestion detection. In our approach, we detect Connected Components or communities of sensors with similarly weighted edges that reflect different states in the traffic, e.g., free flow or congested state, in regions covered by detected sensor groups. We have adapted and implemented the Connected Components and community detection algorithms for detecting groups in the weighted sensor graphs in batch and streaming manner. We evaluate our approach by building and processing the road infrastructure sensor graph for Stockholm's highways using real-world data from the Motorway Control System operated by the Swedish traffic authority. Our results indicate that the Connected Components and DenGraph community detection algorithms can detect congestion with accuracy up to approximate to 94% for Connected Components and up to approximate to 88% for DenGraph. The Louvain Modularity algorithm for community detection fails to detect congestion regions for sparsely connected graphs, representing roads that we have considered in this study. The Hierarchical Clustering algorithm using speed and density readings is able to detect congestion without details, such as shockwaves.

  • 5.
    Abdalmoaty, Mohamed R.
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control.
    Hjalmarsson, Håkan
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control.
    Application of a Linear PEM Estimator to a Stochastic Wiener-Hammerstein Benchmark Problem⁎2018In: IFAC-PapersOnLine, E-ISSN 2405-8963, Vol. 51, no 15, p. 784-789Article in journal (Refereed)
    Abstract [en]

    The estimation problem of stochastic Wiener-Hammerstein models is recognized to be challenging, mainly due to the analytical intractability of the likelihood function. In this contribution, we apply a computationally attractive prediction error method estimator to a real-data stochastic Wiener-Hammerstein benchmark problem. The estimator is defined using a deterministic predictor that is nonlinear in the input. The prediction error method results in tractable expressions, and Monte Carlo approximations are not necessary. This allows us to tackle several issues considered challenging from the perspective of the current mainstream approach. Under mild conditions, the estimator can be shown to be consistent and asymptotically normal. The results of the method applied to the benchmark data are presented and discussed.

  • 6.
    Abdalmoaty, Mohamed R.
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control.
    Hjalmarsson, Håkan
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control.
    Consistent Estimators of Stochastic MIMO Wiener Models based on Suboptimal Predictors2018Conference paper (Refereed)
  • 7.
    Abdalmoaty, Mohamed R.
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control.
    Hjalmarsson, Håkan
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control.
    Linear Prediction Error Methods for Stochastic Nonlinear Models2019In: Automatica, ISSN 0005-1098, E-ISSN 1873-2836, Vol. 105, p. 49-63Article in journal (Refereed)
    Abstract [en]

    The estimation problem for stochastic parametric nonlinear dynamical models is recognized to be challenging. The main difficulty is the intractability of the likelihood function and the optimal one-step ahead predictor. In this paper, we present relatively simple prediction error methods based on non-stationary predictors that are linear in the outputs. They can be seen as extensions of the linear identification methods for the case where the hypothesized model is stochastic and nonlinear. The resulting estimators are defined by analytically tractable objective functions in several common cases. It is shown that, under certain identifiability and standard regularity conditions, the estimators are consistent and asymptotically normal. We discuss the relationship between the suggested estimators and those based on second-order equivalent models as well as the maximum likelihood method. The paper is concluded with a numerical simulation example as well as a real-data benchmark problem.

    The full text will be freely available from 2021-04-01 16:05
  • 8.
    Abdalmoaty, Mohamed R.
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control.
    Rojas, Cristian R.
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control.
    Hjalmarsson, Håkan
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control.
    Identification of a Class of Nonlinear Dynamical Networks⁎2018In: IFAC-PapersOnLine, E-ISSN 2405-8963, Vol. 51, no 15, p. 868-873Article in journal (Refereed)
    Abstract [en]

    Identification of dynamic networks has attracted considerable interest recently. So far the main focus has been on linear time-invariant networks. Meanwhile, most real-life systems exhibit nonlinear behaviors; consider, for example, two stochastic linear time-invariant systems connected in series, each of which has a nonlinearity at its output. The estimation problem in this case is recognized to be challenging, due to the analytical intractability of both the likelihood function and the optimal one-step ahead predictors of the measured nodes. In this contribution, we introduce a relatively simple prediction error method that may be used for the estimation of nonlinear dynamical networks. The estimator is defined using a deterministic predictor that is nonlinear in the known signals. The estimation problem can be defined using closed-form analytical expressions in several non-trivial cases, and Monte Carlo approximations are not necessarily required. We show, that this is the case for some block-oriented networks with no feedback loops and where all the nonlinear modules are polynomials. Consequently, the proposed method can be applied in situations considered challenging by current approaches. The performance of the estimation method is illustrated on a numerical simulation example.

  • 9.
    Abdelmassih, Christian
    KTH, School of Electrical Engineering and Computer Science (EECS).
    Container Orchestration in Security Demanding Environments at the Swedish Police Authority2018Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    The adoption of containers and container orchestration in cloud computing is motivated by many aspects, from technical and organizational to economic gains. In this climate, even security demanding organizations are interested in such technologies but need reassurance that their requirements can be satisfied. The purpose of this thesis was to investigate how separation of applications could be achieved with Docker and Kubernetes such that it may satisfy the demands of the Swedish Police Authority.

    The investigation consisted of a literature study of research papers and official documentation as well as a technical study of iterative creation of Kubernetes clusters with various changes. A model was defined to represent the requirements for the ideal separation. In addition, a system was introduced to classify the separation requirements of the applications.

    The result of this thesis consists of three architectural proposals for achieving segmentation of Kubernetes cluster networking, two proposed systems to realize the segmentation, and one strategy for providing host-based separation between containers. Each proposal was evaluated and discussed with regard to suitability and risks for the Authority and parties with similar demands. The thesis concludes that a versatile application isolation can be achieved in Docker and Kubernetes. Therefore, the technologies can provide a sufficient degree of separation to be used in security demanding environments.

  • 10.
    Abdelmotteleb, Ibtihal
    KTH, School of Electrical Engineering and Computer Science (EECS).
    Designing Electricity Distribution Network Charges for an Efficient Integration of Distributed Energy Resources and Customer Response2018Doctoral thesis, monograph (Other academic)
    Abstract [en]

    A significant transformation has been gradually taking place within the energy sector, mainly as a result of energy policies targeting environmental objectives. Consequently, the penetration of Distributed Energy Resources (DERs) has been escalating, including self-generation, demand side management, storage, and electrical vehicles. Although the integration of DERs may create technical challenges in the operation of distribution networks, it may also provide opportunities to more efficiently manage the network and defer network reinforcements. These opportunities and challenges impose the necessity of redesigning distribution network charges to incentivize efficient customer response.

    This PhD thesis focuses on the design of distribution network charges that send correct economic signals and trigger optimal responses within the context of active customers. First, a cost-reflective network charge is proposed that consists of a forward-looking locational component based on the network’s utilization level, which transmits the long-term incremental cost of network upgrades. Then, a residual cost component that recovers the remaining part of the regulated network revenues is proposed. The objective of the proposed network charge is to increase the system’s efficiency by incentivizing efficient short- and long-term customers’ reaction while ensuring network cost recovery. The Thesis presents an optimization model that simulates customers’ response to the proposed network charge in comparison to other traditional network charge designs. The model considers the operational and DER investment decisions that customers take rationally to minimize their total costs.

    Secondly, an evaluation methodology based on the Analytical Hierarchy Process technique is proposed in order to assess and compare different designs of network charges with respect to four attributes: network cost recovery, deferral of network costs, efficient customer response and recognition of side-effects on customers.

    Finally, a framework for Local Flexibility Mechanisms (LFM) is presented, complementing the proposed cost-reflective network charge. It aims to provide distribution-level coordination to mitigate unintended customer responses to network charges, by allowing customers to reveal their preferences and offer their flexibility services. It consists of a short-term LFM that utilizes customers’ flexibility in day-to-day network operation, and a long-term LFM that procures customers’ long-term flexibility to replace partially or fully network investments in network planning.

  • 11. Abedifar, V.
    et al.
    Furdek, Marija
    KTH, School of Electrical Engineering and Computer Science (EECS), Communication Systems, CoS, Optical Network Laboratory (ON Lab).
    Muhammad, Ajmal
    KTH, School of Electrical Engineering and Computer Science (EECS), Communication Systems, CoS, Optical Network Laboratory (ON Lab).
    Eshghi, M.
    Wosinska, Lena
    KTH, School of Electrical Engineering and Computer Science (EECS), Communication Systems, CoS, Optical Network Laboratory (ON Lab).
    Routing, modulation format, spectrum and core allocation in SDM networks based on programmable filterless nodes2018In: Optics InfoBase Conference Papers, Optics Info Base, Optical Society of America, 2018Conference paper (Refereed)
    Abstract [en]

    An RMSCA approach based on binary particle swarm optimization is proposed for programmable filterless SDM networks, aimed at minimizing core and spectrum usage. Nearoptimal resource consumption.

  • 12. Abedifar, Vahid
    et al.
    Furdek, Marija
    KTH, School of Electrical Engineering and Computer Science (EECS).
    Muhammad, Ajmal
    KTH, School of Electrical Engineering and Computer Science (EECS).
    Eshghi, Mohammad
    Wosinska, Lena
    KTH, School of Electrical Engineering and Computer Science (EECS).
    Routing, Modulation and Spectrum Assignment in Programmable Networks based on Optical White Boxes2018In: Journal of Optical Communications and Networking, ISSN 1943-0620, E-ISSN 1943-0639, Vol. 10, no 9, p. 723-735Article in journal (Refereed)
    Abstract [en]

    Elastic optical networks (EONs) can help overcome the flexibility challenges imposed by emerging heterogeneous and bandwidth-intensive applications. Among the different solutions for flexible optical nodes, optical white box switches implemented by architecture on demand (AoD) have the capability to dynamically adapt their architecture and module configuration to the switching and processing requirements of the network traffic. Such adaptability allows for unprecedented flexibility in balancing the number of required nodal components in the network, spectral resource usage, and length of the established paths. To investigate these trade-offs and achieve cost-efficient network operation, we formulate the routing, modulation, and spectrum assignment (RMSA) problem in AoD-based EONs and propose three RMSA strategies aimed at optimizing a particular combination of these performance indicators. The strategies rely on a newly proposed internal node configuration matrix that models the structure of optical white box nodes in the network, thus facilitating hardware-aware routing of connection demands. The proposed strategies are evaluated in terms of the number of required modules and the related cost, spectral resource usage, and average path length. Extensive simulation results show that the proposed RMSA strategies can achieve remarkable cost savings by requiring fewer switching modules than the benchmarking approaches, at a favorable trade-off with spectrum usage and path length.

  • 13.
    Abedin, Ahmad
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Electronics, Integrated devices and circuits.
    Zurauskaite, Laura
    KTH, School of Electrical Engineering and Computer Science (EECS), Electronics, Integrated devices and circuits.
    Asadollahi, Ali
    KTH, School of Electrical Engineering and Computer Science (EECS), Electronics, Integrated devices and circuits. KTH.
    GOI fabrication for Monolithic 3D integrationIn: Article in journal (Other academic)
  • 14.
    Abedin, Ahmad
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Electronics.
    Zurauskaite, Laura
    KTH, School of Electrical Engineering and Computer Science (EECS), Electronics.
    Asadollahi, Ali
    KTH, School of Electrical Engineering and Computer Science (EECS), Electronics.
    Garidis, Konstantinos
    KTH, School of Electrical Engineering and Computer Science (EECS), Electronics.
    Jayakumar, Ganesh
    KTH, School of Electrical Engineering and Computer Science (EECS), Electronics.
    Malm, B. Gunnar
    KTH, School of Electrical Engineering and Computer Science (EECS), Electronics.
    Hellström, Per-Erik
    KTH, School of Electrical Engineering and Computer Science (EECS), Electronics.
    Östling, Mikael
    KTH, School of Electrical Engineering and Computer Science (EECS).
    Germanium on Insulator Fabrication for Monolithic 3-D Integration2018In: IEEE Journal of the Electron Devices Society, ISSN 2168-6734, Vol. 6, no 1, p. 588-593Article in journal (Refereed)
    Abstract [en]

    A low temperature (T-max = 350 degrees C) process for Germanium (Ge) on insulator (GOI) substrate fabrication with thicknesses of less than 25 nm is reported in this paper. The process is based on a single step epitaxial growth of a Ge/SiGe/Ge stack on Si, room temperature wafer bonding and an etch-back process using Si0.5Ge0.5 as an etch-stop layer. GOI substrates with surface roughness below 0.5 nm, 0.15% tensile strain, thickness nonuniformity of less than 3 nm and residual p-type doping of less than 1016 cm(-3) were fabricated. Ge pFETs are fabricated (T-max = 600 degrees C) on the GOI wafer with 70% yield. The devices exhibit a negative threshold voltage of -0.18 V and 60% higher mobility than the SOI pFET reference devices.

  • 15.
    Abedin, Ahmad
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Electronics.
    Zurauskaite, Laura
    KTH, School of Electrical Engineering and Computer Science (EECS), Electronics.
    Asadollahi, Ali
    KTH, School of Electrical Engineering and Computer Science (EECS), Electronics.
    Garidis, Konstantinos
    KTH, School of Electrical Engineering and Computer Science (EECS), Electronics.
    Jayakumar, Ganesh
    KTH, School of Electrical Engineering and Computer Science (EECS), Electronics.
    Malm, B. Gunnar
    KTH, School of Electrical Engineering and Computer Science (EECS), Electronics.
    Hellström, Per-Erik
    KTH, School of Electrical Engineering and Computer Science (EECS), Electronics.
    Östling, Mikael
    KTH, School of Electrical Engineering and Computer Science (EECS), Electronics.
    GOI fabrication for monolithic 3D integration2018In: 2017 IEEE SOI-3D-Subthreshold Microelectronics Unified Conference, S3S 2017, Institute of Electrical and Electronics Engineers (IEEE), 2018, Vol. 2018, p. 1-3Conference paper (Refereed)
    Abstract [en]

    A low temperature (Tmax=350 °C) process for Ge on insulator (GOI) substrate fabrication with thicknesses of less than 25 nm is reported in this work. The process is based on a single step epitaxial growth of a Ge/SiGe/Ge stack on Si, room temperature wafer bonding, and an etch-back process using Si0.5Ge0.5 as an etch-stop layer. Using this technique, GOI substrates with surface roughness below 0.5 nm, thickness nonuniformity of less than 3 nm, and residual p-type doping of less than 1016 cm-3 are achieved. Ge pFETs are fabricated (Tmax=600 °C) on the GOI wafer with 70% yield. The devices exhibit a negative threshold voltage of-0.18 V and 60% higher mobility than the SOI pFET reference devices.

  • 16.
    Abgrall, Corentin
    KTH, School of Electrical Engineering and Computer Science (EECS).
    Deep learning models as advisors to execute trades on financial markets2018Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Recent work has shown that convolutional networks can successfully handle time series as input in various different problems. This thesis embraces this observation and introduces a new method combining machine learning techniques in order to create profitable trading strategies. The method addresses a binary classification problem: given a specific time, access to prices before this moment and an exit policy, the goal is to forecast the next price movement. The classification method is based on convolutional networks combining two major improvements: a special form of bagging and a weight propagation, to enhance the accuracy and reduce the overall variance of the model. The rolling learning and the convolutional layers are able to exploit the time dependency to strongly improve the trading strategy. The presented architecture is able to surpass the expert traders.

  • 17.
    Aboode, Adam
    KTH, School of Electrical Engineering and Computer Science (EECS).
    Anomaly Detection in Time Series Data Based on Holt-Winters Method2018Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    In today's world the amount of collected data increases every day, this is a trend which is likely to continue. At the same time the potential value of the data does also increase due to the constant development and improvement of hardware and software. However, in order to gain insights, make decisions or train accurate machine learning models we want to ensure that the data we collect is of good quality. There are many definitions of data quality, in this thesis we focus on the accuracy aspect.

    One method which can be used to ensure accurate data is to monitor for and alert on anomalies. In this thesis we therefore suggest a method which, based on historic values, is able to detect anomalies in time series as new values arrive. The method consists of two parts, forecasting the next value in the time series using Holt-Winters method and comparing the residual to an estimated Gaussian distribution.

    The suggested method is evaluated in two steps. First, we evaluate the forecast accuracy for Holt-Winters method using different input sizes. In the second step we evaluate the performance of the anomaly detector when using different methods to estimate the variance of the distribution of the residuals. The results indicate that the suggested method works well most of the time for detection of point anomalies in seasonal and trending time series data. The thesis also discusses some potential next steps which are likely to further improve the performance of this method.

  • 18.
    Abrahamsson, Felix
    KTH, School of Electrical Engineering and Computer Science (EECS).
    Designing a Question Answering System in the Domain of Swedish Technical Consulting Using Deep Learning2018Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Question Answering systems are greatly sought after in many areas of industry. Unfortunately, as most research in Natural Language Processing is conducted in English, the applicability of such systems to other languages is limited. Moreover, these systems often struggle in dealing with long text sequences.

    This thesis explores the possibility of applying existing models to the Swedish language, in a domain where the syntax and semantics differ greatly from typical Swedish texts. Additionally, the text length may vary arbitrarily. To solve these problems, transfer learning techniques and state-of-the-art Question Answering models are investigated. Furthermore, a novel, divide-and-conquer based technique for processing long texts is developed.

    Results show that the transfer learning is partly unsuccessful, but the system is capable of perform reasonably well in the new domain regardless. Furthermore, the system shows great performance improvement on longer text sequences with the use of the new technique.

  • 19.
    Abramson, Alex
    et al.
    MIT, Dept Chem Engn, Cambridge, MA 02139 USA.;MIT, David H Koch Inst Integrat Canc Res, Cambridge, MA 02139 USA..
    Caffarel-Salvador, Ester
    MIT, Dept Chem Engn, Cambridge, MA 02139 USA.;MIT, David H Koch Inst Integrat Canc Res, Cambridge, MA 02139 USA.;MIT, Inst Med Engn & Sci, 77 Massachusetts Ave, Cambridge, MA 02139 USA..
    Khang, Minsoo
    MIT, Dept Chem Engn, Cambridge, MA 02139 USA.;MIT, David H Koch Inst Integrat Canc Res, Cambridge, MA 02139 USA..
    Dellal, David
    MIT, Inst Med Engn & Sci, 77 Massachusetts Ave, Cambridge, MA 02139 USA..
    Silverstein, David
    MIT, Dept Chem Engn, Cambridge, MA 02139 USA.;MIT, David H Koch Inst Integrat Canc Res, Cambridge, MA 02139 USA..
    Gao, Yuan
    MIT, Dept Chem Engn, Cambridge, MA 02139 USA.;MIT, David H Koch Inst Integrat Canc Res, Cambridge, MA 02139 USA..
    Frederiksen, Morten Revsgaard
    Novo Nordisk AS, Global Res Technol, Global Drug Discovery & Device R&D, Copenhagen, Denmark..
    Vegge, Andreas
    Novo Nordisk AS, Global Res Technol, Global Drug Discovery & Device R&D, Copenhagen, Denmark..
    Hubalek, Frantisek
    Novo Nordisk AS, Global Res Technol, Global Drug Discovery & Device R&D, Copenhagen, Denmark..
    Water, Jorrit J.
    Novo Nordisk AS, Global Res Technol, Global Drug Discovery & Device R&D, Copenhagen, Denmark..
    Friderichsen, Anders V.
    Novo Nordisk AS, Global Res Technol, Global Drug Discovery & Device R&D, Copenhagen, Denmark..
    Fels, Johannes
    Novo Nordisk AS, Global Res Technol, Global Drug Discovery & Device R&D, Copenhagen, Denmark..
    Kirk, Rikke Kaae
    Novo Nordisk AS, Global Res Technol, Global Drug Discovery & Device R&D, Copenhagen, Denmark..
    Cleveland, Cody
    MIT, Dept Chem Engn, Cambridge, MA 02139 USA.;MIT, David H Koch Inst Integrat Canc Res, Cambridge, MA 02139 USA.;Novo Nordisk AS, Global Res Technol, Global Drug Discovery & Device R&D, Copenhagen, Denmark..
    Collins, Joy
    MIT, Dept Chem Engn, Cambridge, MA 02139 USA.;MIT, David H Koch Inst Integrat Canc Res, Cambridge, MA 02139 USA..
    Tamang, Siddartha
    MIT, Dept Chem Engn, Cambridge, MA 02139 USA.;MIT, David H Koch Inst Integrat Canc Res, Cambridge, MA 02139 USA..
    Hayward, Alison
    MIT, Dept Chem Engn, Cambridge, MA 02139 USA.;MIT, David H Koch Inst Integrat Canc Res, Cambridge, MA 02139 USA.;MIT, Div Comparat Med, Cambridge, MA 02139 USA..
    Landh, Tomas
    Novo Nordisk AS, Global Res Technol, Global Drug Discovery & Device R&D, Copenhagen, Denmark..
    Buckley, Stephen T.
    Novo Nordisk AS, Global Res Technol, Global Drug Discovery & Device R&D, Copenhagen, Denmark..
    Roxhed, Niclas
    KTH, School of Electrical Engineering and Computer Science (EECS), Micro and Nanosystems.
    Rahbek, Ulrik
    Novo Nordisk AS, Global Res Technol, Global Drug Discovery & Device R&D, Copenhagen, Denmark..
    Langer, Robert
    MIT, Dept Chem Engn, Cambridge, MA 02139 USA.;MIT, David H Koch Inst Integrat Canc Res, Cambridge, MA 02139 USA.;MIT, Inst Med Engn & Sci, 77 Massachusetts Ave, Cambridge, MA 02139 USA.;MIT, Media Lab, Cambridge, MA 02139 USA..
    Traverso, Giovanni
    MIT, Dept Chem Engn, Cambridge, MA 02139 USA.;MIT, David H Koch Inst Integrat Canc Res, Cambridge, MA 02139 USA.;MIT, Dept Mech Engn, Cambridge, MA 02139 USA.;Harvard Med Sch, Brigham & Womens Hosp, Div Gastroenterol, Boston, MA 02115 USA..
    An ingestible self-orienting system for oral delivery of macromolecules2019In: Science, ISSN 0036-8075, E-ISSN 1095-9203, Vol. 363, no 6427, p. 611-+Article in journal (Refereed)
    Abstract [en]

    Biomacromolecules have transformed our capacity to effectively treat diseases; however, their rapid degradation and poor absorption in the gastrointestinal (GI) tract generally limit their administration to parenteral routes. An oral biologic delivery system must aid in both localization and permeation to achieve systemic drug uptake. Inspired by the leopard tortoise's ability to passively reorient, we developed an ingestible self-orienting millimeter-scale applicator (SOMA) that autonomously positions itself to engage with GI tissue. It then deploys milliposts fabricated from active pharmaceutical ingredients directly through the gastric mucosa while avoiding perforation. We conducted in vivo studies in rats and swine that support the applicator's safety and, using insulin as a model drug, demonstrated that the SOMA delivers active pharmaceutical ingredient plasma levels comparable to those achieved with subcutaneous millipost administration.

  • 20.
    Abrardo, Andrea
    et al.
    Univ Siena, Dipartimento Ingn Informaz, I-53100 Siena, Italy..
    Fodor, Gabor
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control.
    Moretti, Marco
    Univ Pisa, Dipartimento Ingn Informaz, I-50126 Pisa, Italy..
    Telek, Miklos
    Budapest Univ Technol & Econ, Dept Networked Syst & Serv, H-1117 Budapest, Hungary.;MTA BME Informat Syst Res Grp, H-1117 Budapest, Hungary..
    MMSE Receiver Design and SINR Calculation in MU-MIMO Systems With Imperfect CSI2019In: IEEE Wireless Communications Letters, ISSN 2162-2337, E-ISSN 2162-2345, Vol. 8, no 1, p. 269-272Article in journal (Refereed)
    Abstract [en]

    The performance of the uplink of multiuser multiple input multiple output systems depends critically on the receiver architecture and on the quality of the acquired channel state information. A popular approach is to design linear receivers that minimize the mean squared error (MSE) of the received data symbols. Unfortunately, most of the literature does not take into account the presence of channel state information errors in the MSE minimization. In this letter we develop a linear minimum MSE (MMSE) receiver that employs the noisy instantaneous channel estimates to minimize the MSE, and highlight the dependence of the receiver performance on the pilot-to-data power ratio. By invoking the theory of random matrices, we calculate the users' signal-to-interference-plus-noise ratio as a function of the number of antennas and the pilot-to-data power ratio of all users. Numerical results indicate that this new linear receiver outperforms the classical mismatched MMSE receiver.

  • 21.
    Ackland, Marcus
    KTH, School of Electrical Engineering and Computer Science (EECS).
    Investigating Adaptive Trajectories to Explore Water Plumes on Icy Moons2018Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    This thesis investigates different means of introducing autonomy intodesigning spacecraft trajectories by surveying four different adaptivetrajectories. This is done using established algorithms within pathplanning and robotics, implementing trajectories based on splines andgreedy algorithms. The survey is based on real planetary data lettingthe spacecraft fly through the water plumes on Enceladus. Theseplumes are constructed using analytical models of the water plumesthat have been fitted to measurements made by Cassini during flybysover the last decade. A mission designed to probe these plumes at analtitude as low as 5 km is studied as a test scenario for the adaptive trajectories.It is found that the adaptive trajectories increase the sciencereturn at lower altitudes, both in exploring the terrain and samplingthe plume material.

  • 22.
    Adaldo, Antonio
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control.
    Event-triggered and cloud-support control of multi-robot systems2018Doctoral thesis, monograph (Other academic)
    Abstract [en]

    In control of multi-robot systems, the aim is to obtain a coordinated behavior through local interactions among the robots. A multi-agent system is an abstract model of a multi-robot system. In this thesis, we investigate multi-agent systems where inter-agent communication is modeled by discrete events triggered by conditions on the internal state of the agents. We consider two models of communication. In the first model, two agents exchange information directly with each other. In the second model, all information is exchanged asynchronously over a shared repository. Four contributions on control algorithms for multi-agent systems are offered in the thesis. The first contribution is an event-triggered pinning control algorithm for a network of agents with nonlinear dynamics and time-varying topology. Pinning control is a strategy to steer the behavior of the system in a desired manner by controlling only a small fraction of the agents. We express the controllability of the network in terms of an average value of the network connectivity over time, and we show that all the agents can be driven to a desired reference trajectory. The second contribution is a control algorithm for multi-agent systems where inter-agent communication is substituted with a shared remote repository hosted on a cloud. The communication between each agent and the cloud is modeled as a sequence of events scheduled recursively by the agent. We quantify the connectivity of the network and we show that it is possible to synchronize the multi-agent system to the same state trajectory, while guaranteeing that two consecutive cloud accesses by the same agent are separated by a lower-bounded time interval. The third contribution is a family of distributed controllers for coverage and surveillance tasks with a network of mobile agents with anisotropic sensing patterns. We develop an abstract model of the environment under inspection and define a measure of the coverage attained by the sensor network. We show that the network attains nondecreasing coverage, and we characterize the equilibrium configurations of the network. The fourth contribution is a distributed, cloud-supported control algorithm for inspection of 3D structures with a network of mobile sensing agents, similar to those considered in the third contribution. We develop an abstract model of the structure to inspect and quantify the degree of completion of the inspection. We demonstrate that, under the proposed algorithm, the network is guaranteed to complete the inspection in finite time. All results presented in the thesis are corroborated by numerical simulations and sometimes by experiments with aerial robotic platforms. The experiments show that the theory and methods developed in the thesis are of practical relevance.

  • 23.
    Adaldo, Antonio
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control.
    Dimarogonas, Dimos V.
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control.
    Johansson, Karl Henrik
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control.
    Cloud-supported effective coverage of 3D structures2018In: 2018 European Control Conference, ECC 2018, Institute of Electrical and Electronics Engineers (IEEE), 2018, p. 95-100, article id 8550377Conference paper (Refereed)
    Abstract [en]

    In this paper, we present a distributed algorithm for cloud-supported effective coverage of 3D structures with a network of sensing agents. The structure to inspect is abstracted into a set of landmarks, where each landmark represents a point or small area of interest, and incorporates information about position and orientation. The agents navigate the environment following the proposed control algorithm until all landmarks have reached a satisfactory level of coverage. The agents do not communicate with each other directly, but exchange data through a shared cloud repository which is accessed asynchronously and intermittently. We show formally that, under the proposed control architecture, the networked agents complete the coverage mission in finite time. The results are corroborated by simulations in ROS, and experimental evaluation is in progress.

  • 24.
    Adaldo, Antonio
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Liuzza, Davide
    Univ Sannio, Dept Engn, I-82100 Benevento, Italy..
    Dimarogonas, Dimos V.
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Johansson, Karl H.
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre. KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control.
    Cloud-Supported Formation Control of Second-Order Multiagent Systems2018In: IEEE Transactions on Big Data, ISSN 2325-5870, E-ISSN 2168-6750, Vol. 5, no 4, p. 1563-1574Article in journal (Refereed)
    Abstract [en]

    This paper addresses a formation problem for a network of autonomous agents with second-order dynamics and bounded disturbances. Coordination is achieved by having the agents asynchronously upload (download) data to (from) a shared repository, rather than directly exchanging data with other agents. Well-posedness of the closed-loop system is demonstrated by showing that there exists a lower bound for the time interval between two consecutive agent accesses to the repository. Numerical simulations corroborate the theoretical results.

  • 25.
    Adam, Jonathan
    KTH, School of Electrical Engineering and Computer Science (EECS), Media Technology and Interaction Design, MID.
    Analyzing Function and Potential in Cuba's El Paquete: A Postcolonial Approach2018Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    The dire state of Cuban internet connectivity has inspired local informal innovations. One such innovation is El Paquete, a weekly distribution of downloaded content spread through an informal network. Taking a postcolonial approach, I investigate through user experiences how this network operates in a resource-poor environment. This investigation articulates a model of El Paquete centered on social interactions, which inform the system’s function but also shape El Paquete’s design and role in society. Based on this model, a set of speculative design exercises probe possibilities to streamline El Paquete’s compilation, involve consumer preferences in its design directions, or act as a disruption tolerant network. In uncovering the technical possibilities of El Paquete, these designs illuminate how its current design serves Cuban communities by embodying realities and limitations of Cuban society. El Paquete’s embodiment of informal innovation serves as a call to designers to continuously rethink development design processes, centering communities and their knowledge and technical practices.

  • 26.
    Adamsson, Marcus
    KTH, School of Electrical Engineering and Computer Science (EECS).
    Curriculum learning for increasing the performance of a reinforcement learning agent in a static first-person shooter game2018Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    In this thesis, we trained a reinforcement learning agent using one of the most recent policy gradient methods, proximal policy optimization, in a first-person shooter game with a static player. We investigated how curriculum learning can be used to increase performance of a reinforcement learning agent. Two reinforcement learning agents were trained in two different environments. The first environment was constructed without curriculum learning and the second environment was with curriculum learning. After training the agents, the agents were placed in the same environment where we compared them based on their performance. The performance was measured by the achieved cumulative reward. The result showed that there is a difference in performance between the agents. It was concluded that curriculum learning can be used to increase the performance of a reinforcement learning agent in a first-person shooter game with a static player.

  • 27.
    Aden Hassan, Abdullahi
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS).
    Karlsson Källqvist, Rasmus
    KTH, School of Electrical Engineering and Computer Science (EECS).
    Evaluating LoRa Physical as a Radio Link Technology for use in a Remote-Controlled Electric Switch System for a Network Bridge Radio-Node2019Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    This report explores the design of a system for remotely switching electronics on and off within a range of at least 15 km, to be used with battery driven radio nodes for outdoor Wi-Fi network bridging. The application of the network bridges are connecting to remote networks, should Internet infrastructure fail during an emergency.The problem statement for the report was “What is a suitable radio link technology for use in a remote controlled electrical switch system and how should it best be put to use?” To answer the question, delimitation was done to exploring Low Power Wide Area Network (LPWAN) link technologies, due to their prior use within power constrained devices.Long Range-radio, abbreviated LoRa, is a LPWAN radio modulation technique and was determined to be a good candidate as a suitable link technology for the remote electrical switch system. The range of LoRa is achieved by drastically lowering the data rate of the transmission, and is suitable for battery-powered or energy harvesting devices such as those found in the field of Internet of Things.A LoRa-based transmitter and receiver pair was implemented, and measured to have a packet delivery ratio of over 95% at a distance of 2 km, measured between two bridges. Data at further distances could not be accurately determined, because of the LoRa transceiver giving faulty readings.No conclusion could be made about the suitability for using a LoRa based system to solve the problem, partially due to an improper method for testing the radio performance was used, and partially due to an inconclusive measurement result.

  • 28.
    Adlers, Jacob
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS).
    Pihl, Gustaf
    KTH, School of Electrical Engineering and Computer Science (EECS).
    Prediction of training time for deep neural networks in TensorFlow2018Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    Machine learning has gained a lot of interest over the past years and is now used extensively in various areas. Google has developed a framework called TensorFlow which simplifies the usage of machine learning without compromising the end result. However, it does not resolve the issue of neural network training being time consuming. The purpose of this thesis is to investigate with what accuracy training times can be predicted using TensorFlow. Essentially, how effectively one neural network in TensorFlow can be used to predict the training times of other neural networks, also in TensorFlow. In order to do this, training times for training different neural networks was collected. This data was used to create a neural network for prediction. The resulting neural network is capable of predicting training times with an average accuracy of 93.017%.

  • 29.
    Adolfsson, Alexander
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS).
    Arrhenius, Daniel
    KTH, School of Electrical Engineering and Computer Science (EECS).
    Overseeing Intersection System for Autonomous Vehicle Guidance2019Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    Intersections represents one of the most common accident sites in traffic today. The biggest cause of accidents is obstructed view and subpar communication between vehicles. Since autonomous vehicles rely on sensors that require a direct view intersections are some of the most complex situations. Where the potential for inter vehicular communication exists between modern vehicles, it is absent in the older generation. An overseeing intersection system can fill this function during the transition period to fully autonomous traffic. This project aimed to implement an intersection system to assist autonomous vehicles through a crossroad. The assist system’s objective was to collect and transmit data from cars close to the junction to the autonomous vehicles nearby. The concept was tested in simulations by having models traverse a crossroad to evaluate how it utilised the external information. No persistent conclusion could be made due to insufficient simulation environment and vehicle model control.

  • 30.
    Adolfsson, Fredrik
    KTH, School of Electrical Engineering and Computer Science (EECS).
    WebTaint: Dynamic Taint Tracking for Java-based Web Applications2018Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    The internet is a source of information and it connects the world through a single platform. Many businesses have taken advantage of this to share information, to communicate with customers, and to create new business opportunities. However, this does not come without drawbacks as there exists an elevated risk to become targeted in attacks.

    The thesis implemented a dynamic taint tracker, named WebTaint, to detect and prevent confidentiality and integrity vulnerabilities in Java-based web applications. We evaluated to what extent WebTaint can combat integrity vulnerabilities. The possible advantages and disadvantages of using the application is introduced as well as an explication whether the application was capable of being integrated into production services.

    The results show that WebTaint helps to combat SQL Injection and Cross-Site Scripting attacks. However, there are drawbacks in the form of additional time and memory overhead. The implemented solution is therefore not suitable for time or memory sensitive domains. WebTaint could be recommended for use in test environments where security experts utilize the taint tracker to find TaintExceptions through manual and automatic attacks.

  • 31.
    Adrup, Joakim
    KTH, School of Electrical Engineering and Computer Science (EECS).
    Visualization and Interaction with Temporal Data using Data Cubes in the Global Earth Observation System of Systems2018Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    The purpose of this study was to explore the usage of data cubes in the context of the Global Earth Observation System of Systems (GEOSS). This study investigated what added benefit could be provided to users of the GEOSS platform by utilizing the capabilities of data cubes. Data cubes in earth observation is a concept for how data should be handled and provided by a data server. It includes aspects such as flexible extraction of subsets and processing capabilities. In this study it was found that the most frequent use case for data cubes was time analysis. One of the main services provided by the GEOSS portal was the discovery and inspection of datasets. In the study a timeline interface was constructed to facilitate the exploration and inspection of datasets with a temporal dimension. The datasets were provided by a data cube, and made use of the data cubes capabilities in retrieving subsets of data along any arbitrary axis. A usability evaluation was conducted on the timeline interface to gain insight into the users requirements and user satisfaction. The results showed that the design worked well in many regards, ranking high in user satisfaction. On a number of points the study highlighted areas of improvement. Providing insight into important design limitations and challenges together with suggestions on how these could be approached in different ways.

  • 32.
    Afework, Miriam
    KTH, School of Electrical Engineering and Computer Science (EECS), Media Technology and Interaction Design, MID.
    Using Magic Machines to Elaborate Menstrual Self-Tracker­s for Women with Endometriosis2018Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Existing self-tracking tools for women concentrate on one’s general well-being and keeping track of ovulation and periods. With around 10% of women worldwide suffering from endometriosis there is an unmet need to leverage self-tracking for women whose cycles are affected by more variables. The disease is enigmatic with an unknown cause and cure and the ill­ness differs for each individual in symptoms and working treatments. It is therefore critical to understand how women can learn about their bodies and how to treat their condition. In this research I work with two sufferers to identify their secret de­sires through a workshop and a series of interviews. Results suggest that women with endometriosis could benefit from ex­perimenting with different habits and make personalized routines to suit their own needs. Finally I present design implica­tions for an existing menstrual app in the form of an add-on. The steps of the add-on tool included three steps. Firstly, choosing variables of one’s well being to track (mood, energy, pain etc.), choosing activities for one or more cycles (gluten-free diet, exercising etc.), and lastly viewing an analysis of any changes in the body.

  • 33.
    Afrem, Bassel
    KTH, School of Electrical Engineering and Computer Science (EECS).
    Designing a Suitable Help Desk Software2019Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    In growing help desk companies, how to handle customer requests is a mark of success. Thus, each company should have an organized system to efficiently handle the communication between the company and its customers.There are many variants of help desk service software that serve different kinds of business model. Therefore, this thesis will be a study about what types of help desk software there are and what functionalities they have, in order to reach the goal of the project which was designing a suitable help desk software for a company Amplius Field Services, based on its business model.The chosen method to solve the problem consisted of a literature study about help desk software and business models, followed by a case study about the different types of help desk software that are already developed and provided and what functions they fulfill by analyzing their pros and cons and evaluate the kind of functionalities they serve. Then, based on the performed study, a general model for a help desk software containing the most important functionalities, was provided. The provided general model should be basically applicable for all different help desk companies, with possibility to be improved by adding other functionalities as required or desired by the company itself. It is intended to companies that desire to build their own application. Finally, the general model was applied for Amplius after studying its business model.The result of the project was finding a general design of a help desk software based on the result of the case study, then, the model was applied to Amplius after setting the requirements through studying its business model’s components. This gave the tailored design for Amplius, and it was supposed to be implemented and tested, but the project time was not sufficient.

  • 34.
    Ahlberg, Carl Daniel
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS).
    Mauritz, Wera
    KTH, School of Electrical Engineering and Computer Science (EECS).
    Modeling Far Ultraviolet Auroral Ovals at Ganymede2018Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    Ganymede, one of Jupiters moons, differs from other moons in the Solar System as it has its own magnetic field. This rare property shapes the morphology on the existing far ultraviolet oxygen auroral ovals on the celestial body in the northern and southern hemisphere created by high energy electrons colliding into the atmosphere.With the help of the Hubble Space Telescope (HST) this phenomenon has been captured and analyzed multiple times during the past 20 years using the on-board Space Telescope Imaging Spectrograph (STIS). The ultimate goal of this project is recreating the far ultraviolet oxygen auroral emissions on Ganymede as a 3D computer model in MATLAB by using the data recovered from HST.The method used to reach this goal was to implement a model with main characteristics of the auroral ovals, project it onto a plane and then use a Cauchy distribution to filter the model. To compare the model with images from HST, a χ2-value was calculated for every pixel in each image. To further improvethe model the Nelder-Mead Simplex optimization method was applied.The project succeeded in such a way that the final model created views of the locations and the appearance of the bright spots that represent the auroral ovals around Ganymede with an accurate result in relation to the given data.

  • 35.
    Ahlberg, Sofie
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control.
    Human-in-the-Loop Control Synthesis for Multi-Agent Systems under Metric Interval Temporal Logic Specifications2019Licentiate thesis, monograph (Other academic)
    Abstract [en]

    With the increase of robotic presence in our homes and work environment, it has become imperative to consider human-in-the-loop systems when designing robotic controllers. This includes both a physical presence of humans as well as interaction on a decision and control level. One important aspect of this is to design controllers which are guaranteed to satisfy specified safety constraints. At the same time we must minimize the risk of not finding solutions, which would force the system to stop. This require some room for relaxation to be put on the specifications. Another aspect is to design the system to be adaptive to the human and its environment.

    In this thesis we approach the problem by considering control synthesis for multi-agent systems under hard and soft constraints, where the human has direct impact on how the soft constraint is violated. To handle the multi-agent structure we consider both a classical centralized automata based framework and a decentralized approach with collision avoidance. To handle soft constraints we introduce a novel metric; hybrid distance, which quantify the violation. The hybrid distance consists of two types of violation; continuous distance or missing deadlines, and discrete distance or spacial violation. These distances are weighed against each other with a weight constant we will denote as the human preference constant. For the human impact we consider two types of feedback; direct feedback on the violation in the form of determining the human preference constant, and direct control input through mixed-initiative control where the human preference constant is determined through an inverse reinforcement learning algorithm based on the suggested and followed paths. The methods are validated through simulations.

  • 36.
    Ahlgren, Lucas
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS).
    Marin Puentes, Angie Melissa
    KTH, School of Electrical Engineering and Computer Science (EECS).
    Livsmedelshandel i webbutiker: En tillgänglighetsundersökning med WCAG 2.02018Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    This study aims to evaluate the state of web accessibility in online grocery stores in Sweden. This with the aim of informing the food industry about how accessibility is prioritized today, in order to contribute, to the discussion about this subject becoming more active. The survey included seven Swedish grocery stores on the web: Ica, Coop, Mat.se, Mathem.se, Willys, Hemköp and City Gross. In each web store, accessibility was evaluated on three web pages: the start page, the product page for 1 liter of milk of the brand Arla and the checkout page. The starting point for evaluat-ing accessibility on these web pages was the WCAG 2.0 web standard, which is the recommended standard from the W3C to evaluate accessibility on the web. The study was conducted using an evaluation tool AChecker as well as manual evaluations. The result showed that there is a lot of difference between different web stores regarding accessibility according to WCAG 2.0 acces-sibility standards. Common to all online stores was that none of them met the lowest level of WCAG 2.0, Level A. City Gross broke against the most number of guidelines while Willys broke against the fewest number of guidelines in WCAG 2.0. Which indicates that accessibility is not a priority in these online grocery stores.

  • 37.
    Ahlström, Marcus
    KTH, School of Electrical Engineering and Computer Science (EECS), Media Technology and Interaction Design, MID.
    Broadening the Reading Experience on Mobile Devices using Tilt-based Input: An Explorative Design Study2018Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    This thesis is an explorative study aimed at the possibility of integrating tilt-based input to improve the reading experience on smartphones. Previous works from the early 2000s have been skeptical towards tilt-based navigation, deeming it unruly and imprecise. To investigate if today’s technology has unlocked new possibilities; two experimental reading methods were designed, created and tested iteratively on 20, respectively 18 participants. The first method is a reassessment of tilt-based auto-scrolling and the second is a novel approach comparable to tilt-based paging. Data from the reading sessions were collected quantitatively in tandem with qualitative data from post-session interviews. The results indicate good potential and a reading performance similar to the standard navigation method. The importance of accommodating people with different reading behaviours was also discussed.

  • 38. Ahmad, S. A.
    et al.
    Naqvi, S. I.
    Khalid, M.
    Amin, Y.
    Loo, J.
    Tenhunen, Hannu
    KTH, School of Electrical Engineering and Computer Science (EECS), Electronics, Integrated devices and circuits.
    Penta-band antenna with defected ground structure for wireless communication applications2019In: 2019 2nd International Conference on Computing, Mathematics and Engineering Technologies, iCoMET 2019, Institute of Electrical and Electronics Engineers Inc. , 2019Conference paper (Refereed)
    Abstract [en]

    This work proposes a compact, penta-band, slotted antenna with Defected Ground Structure (DGS). The proposed multiband resonator is intended for integration into microwave circuits and portable RF portable devices. The prototype with spurlines and DGS is designed on thin Rogers RT Duroid 5880 substrate having thickness 0.508 mm. The presented radiator is capable to cover the frequency bands 2.46-2.59 GHz, 2.99-3.78 GHz, 5.17-5.89 GHz, 6.86-7.36 GHz, 9.38-11 GHz. The impedance bandwidths of 5.24%, 23.68%, 12.8%, 7.24% and 16.08% is obtained for the covered frequency bands respectively. The antenna proposed in this work thus supports WLAN, WiMAX, ISM, LTE, Bluetooth, C-band and X-band applications. The radiator attains 4.2 dB peak gain. It is apparent from the radiation performance of the prototype, that it is an effective candidate for current and forthcoming multiband wireless applications.

  • 39. Ahmed, A. A.
    et al.
    Almeida, Teresa
    KTH, School of Electrical Engineering and Computer Science (EECS), Media Technology and Interaction Design, MID.
    Choi, J. O.
    Pincus, J.
    Ireland, K.
    What’s at issue: Sex, stigma, and politics in ACM publishing2018In: Proceeding CHI EA '18 Extended Abstracts of the 2018 CHI Conference on Human Factors in Computing Systems, Association for Computing Machinery (ACM), 2018, article id alt07Conference paper (Refereed)
    Abstract [en]

    Because publishing with the ACM is essentially required to advance our careers, we must examine its practices critically and constructively. To this end, we reflect on our experience working with the ACM student publication Crossroads. We encountered rigid content limitations related to sex and sexuality, preventing some contributors from foregrounding their connection to political activism, and others from publishing altogether. We explore the underlying institutional and sociopolitical problems and propose starting points for future action, including developing a transparent content approval policy and new organizations for politically-engaged computing researchers, all of which should center the leadership of marginalized individuals.

  • 40. Ahmed, J.
    et al.
    Josefsson, T.
    Johnsson, A.
    Flinta, C.
    Moradi, F.
    Pasquini, R.
    Stadler, Rolf
    KTH, School of Electrical Engineering and Computer Science (EECS), Network and Systems engineering. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, ACCESS Linnaeus Centre.
    Automated diagnostic of virtualized service performance degradation2018In: IEEE/IFIP Network Operations and Management Symposium: Cognitive Management in a Cyber World, NOMS 2018, Institute of Electrical and Electronics Engineers Inc. , 2018, p. 1-9Conference paper (Refereed)
    Abstract [en]

    Service assurance for cloud applications is a challenging task and is an active area of research for academia and industry. One promising approach is to utilize machine learning for service quality prediction and fault detection so that suitable mitigation actions can be executed. In our previous work, we have shown how to predict service-level metrics in real-time just from operational data gathered at the server side. This gives the service provider early indications on whether the platform can support the current load demand. This paper provides the logical next step where we extend our work by proposing an automated detection and diagnostic capability for the performance faults manifesting themselves in cloud and datacenter environments. This is a crucial task to maintain the smooth operation of running services and minimizing downtime. We demonstrate the effectiveness of our approach which exploits the interpretative capabilities of Self- Organizing Maps (SOMs) to automatically detect and localize different performance faults for cloud services. © 2018 IEEE.

  • 41.
    Ahmed, Laeeq
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Computational Science and Technology (CST).
    Georgiev, Valentin
    Capuccini, Marco
    Toor, Salman
    Schaal, Wesley
    Laure, Erwin
    KTH, School of Electrical Engineering and Computer Science (EECS), Computational Science and Technology (CST).
    Spjuth, Ola
    Efficient iterative virtual screening with Apache Spark and conformal prediction2018In: Journal of Cheminformatics, ISSN 1758-2946, E-ISSN 1758-2946, Vol. 10, article id 8Article in journal (Refereed)
    Abstract [en]

    Background: Docking and scoring large libraries of ligands against target proteins forms the basis of structure-based virtual screening. The problem is trivially parallelizable, and calculations are generally carried out on computer clusters or on large workstations in a brute force manner, by docking and scoring all available ligands. Contribution: In this study we propose a strategy that is based on iteratively docking a set of ligands to form a training set, training a ligand-based model on this set, and predicting the remainder of the ligands to exclude those predicted as 'low-scoring' ligands. Then, another set of ligands are docked, the model is retrained and the process is repeated until a certain model efficiency level is reached. Thereafter, the remaining ligands are docked or excluded based on this model. We use SVM and conformal prediction to deliver valid prediction intervals for ranking the predicted ligands, and Apache Spark to parallelize both the docking and the modeling. Results: We show on 4 different targets that conformal prediction based virtual screening (CPVS) is able to reduce the number of docked molecules by 62.61% while retaining an accuracy for the top 30 hits of 94% on average and a speedup of 3.7. The implementation is available as open source via GitHub (https://github.com/laeeq80/spark-cpvs) and can be run on high-performance computers as well as on cloud resources.

  • 42.
    Ahmed, Noman
    KTH, School of Electrical Engineering and Computer Science (EECS).
    Efficient Modeling of Modular Multilevel Converters for HVDC Transmission Systems2018Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    The drive towards getting more and more electrical energy from renewable sources, requires more efficient electric transmission systems. A stronger grid, with more controllability and higher capacity, that can handle power fluctuations due to a mismatch between generation and load is also needed. High-voltage dc (HVDC) provides efficient and economical power transmission over very long distances, and will be a key player in shaping-up the future electric grid. Due to its outstanding features, the modular multilevel converter (MMC) has already been widely accepted as a key converter topology in voltage-source converter (VSC)-based HVDC transmission systems.

    In order to study the feasibility of future MMC-based HVDC grids, adequate simulation models are necessary. The main objective of the thesis is to propose MMC reduced-order simulation models capable of accurately replicating the response of an MMC during all relevant operating conditions. Such models are the basic building blocks in developing efficient simulation models for HVDC grids. This thesis presents two MMC equivalent simulation models, the continuous model (CM) and the detailed equivalent model (DEM). Compared to the CM, the DEM is also capable of demonstrating the individual sumodule behavior of an MMC. These models are validated by comparing with the detailed MMC model as well as with experimental results obtained from an MMC prototype in the laboratory. The most significant feature of the models is the representation of the blocking capability of the MMC, presented for the first time in the literature for an MMC equivalent simulation model. This feature is very important in replicating the accurate transient behavior of an MMC during energization and fault conditions. This thesis also investigates the performance of the MMC with redundant submodules in the arms. Two different control strategies are used and compared for integrating redundant submodules.

    The proposed MMC models are used in developing point-to-point and multiterminal HVDC (MTDC) systems. A reduced-order model of a hybrid HVDC breaker is also developed and employed in the MTDC system, making the test system capable of accurately replicating the behavior of the MMCbased MTDC system employing hybrid HVDC breakers. The conclusion of the analysis of dc-side faults in a MTDC system is that fast-acting HVDC breakers are necessary to isolate only the faulted part in the MTDC system to ensure the power flow in rest of the system is not interrupted.

    A generic four-terminal HVDC grid test system using the CM model is also developed. The simulated system can serve as a standard HVDC grid test system. It is well-suited to electromagnetic transient (EMT) studies in a limited version of commercially available EMT-type software. The dynamic performance of the HVDC grid is studied under different fault conditions.

  • 43.
    Ahmed, War
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS).
    Bahador, Mehrdad
    KTH, School of Electrical Engineering and Computer Science (EECS).
    The accuracy of the LSTM model for predicting the S&P 500 index and the difference between prediction and backtesting2018Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    In this paper the question of the accuracy of the LSTM algorithm for predicting stock prices is being researched. The LSTM algorithm is a form of deep learning algorithm. The algorithm takes in a set of data as inputs and finds a pattern to dissolve an output. Our results point to that using backtesting as the sole method to verify the accuracy of a model can fallible. For the future, researchers should take a fresh approach by using real-time testing. We completed this by letting the algorithm make predictions on future data. For the accuracy of the model we reached the conclusion that having more parameters improves accuracy.

  • 44.
    Ainomae, Ahti
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Bengtsson, Mats
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Trump, Tonu
    Tallinn Univ Technol, Dept Radio & Telecommun Engn, EE-12616 Tallinn, Estonia..
    Distributed Largest Eigenvalue-Based Spectrum Sensing Using Diffusion LMS2018In: IEEE TRANSACTIONS ON SIGNAL AND INFORMATION PROCESSING OVER NETWORKS, ISSN 2373-776X, Vol. 4, no 2, p. 362-377Article in journal (Refereed)
    Abstract [en]

    In this paper, we propose a distributed detection scheme for cognitive radio (CR) networks, based on the largest eigenvalues (LEs) of adaptively estimated correlation matrices (CMs), assuming that the primary user signal is temporally correlated. The proposed algorithm is fully distributed, there by avoiding the potential single point of failure that a fusion center would imply. Different forms of diffusion least mean square algorithms are used for estimating and averaging the CMs over the CR network for the LE detection and the resulting estimation performance is analyzed using a common framework. In order to obtain analytic results on the detection performance, the exact distribution of the CM estimates are approximated by a Wishart distribution, by matching the moments. The theoretical findings are verified through simulations.

  • 45.
    Akhmetova, Dana
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Computational Science and Technology (CST).
    Cebamanos, L.
    Iakymchuk, Roman
    KTH, School of Electrical Engineering and Computer Science (EECS), Computational Science and Technology (CST).
    Rotaru, T.
    Rahn, M.
    Markidis, Stefano
    KTH, School of Electrical Engineering and Computer Science (EECS), Computational Science and Technology (CST).
    Laure, Erwin
    KTH, School of Electrical Engineering and Computer Science (EECS), Computational Science and Technology (CST).
    Bartsch, V.
    Simmendinger, C.
    Interoperability of GASPI and MPI in large scale scientific applications2018In: 12th International Conference on Parallel Processing and Applied Mathematics, PPAM 2017, Springer Verlag , 2018, p. 277-287Conference paper (Refereed)
    Abstract [en]

    One of the main hurdles of a broad distribution of PGAS approaches is the prevalence of MPI, which as a de-facto standard appears in the code basis of many applications. To take advantage of the PGAS APIs like GASPI without a major change in the code basis, interoperability between MPI and PGAS approaches needs to be ensured. In this article, we address this challenge by providing our study and preliminary performance results regarding interoperating GASPI and MPI on the performance crucial parts of the Ludwig and iPIC3D applications. In addition, we draw a strategy for better coupling of both APIs. 

  • 46.
    Aksjonova, Jevgenija
    KTH, School of Electrical Engineering and Computer Science (EECS).
    LDD: Learned Detector and Descriptor of Points for Visual Odometry2018Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Simultaneous localization and mapping is an important problem in robotics that can be solved using visual odometry -- the process of estimating ego-motion from subsequent camera images. In turn, visual odometry systems rely on point matching between different frames. This work presents a novel method for matching key-points by applying neural networks to point detection and description. Traditionally, point detectors are used in order to select good key-points (like corners) and then these key-points are matched using features extracted with descriptors. However, in this work a descriptor is trained to match points densely and then a detector is trained to predict, which points are more likely to be matched with the descriptor. This information is further used for selection of good key-points. The results of this project show that this approach can lead to more accurate results compared to model-based methods.

  • 47.
    Al Ahad, Muhammed Abdullah
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, Centre for High Performance Computing, PDC.
    Simmendinger, Christian
    T Syst Solut Res GmbH, D-70563 Stuttgart, Germany..
    Iakymchuk, Roman
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, Centre for High Performance Computing, PDC.
    Laure, Erwin
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, Centre for High Performance Computing, PDC.
    Markidis, Stefano
    KTH, School of Electrical Engineering and Computer Science (EECS), Centres, Centre for High Performance Computing, PDC.
    Efficient Algorithms for Collective Operations with Notified Communication in Shared Windows2018In: PROCEEDINGS OF PAW-ATM18: 2018 IEEE/ACM PARALLEL APPLICATIONS WORKSHOP, ALTERNATIVES TO MPI (PAW-ATM), IEEE , 2018, p. 1-10Conference paper (Refereed)
    Abstract [en]

    Collective operations are commonly used in various parts of scientific applications. Especially in strong scaling scenarios collective operations can negatively impact the overall applications performance: while the load per rank here decreases with increasing core counts, time spent in e.g. barrier operations will increase logarithmically with the core count. In this article, we develop novel algorithmic solutions for collective operations such as Allreduce and Allgather(V)-by leveraging notified communication in shared windows. To this end, we have developed an extension of GASPI which enables all ranks participating in a shared window to observe the entire notified communication targeted at the window. By exploring benefits of this extension, we deliver high performing implementations of Allreduce and Allgather(V) on Intel and Cray clusters. These implementations clearly achieve 2x-4x performance improvements compared to the best performing MPI implementations for various data distributions.

  • 48.
    Al Hakim, Ezeddin
    KTH, School of Electrical Engineering and Computer Science (EECS).
    3D YOLO: End-to-End 3D Object Detection Using Point Clouds2018Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    For safe and reliable driving, it is essential that an autonomous vehicle can accurately perceive the surrounding environment. Modern sensor technologies used for perception, such as LiDAR and RADAR, deliver a large set of 3D measurement points known as a point cloud. There is a huge need to interpret the point cloud data to detect other road users, such as vehicles and pedestrians.

    Many research studies have proposed image-based models for 2D object detection. This thesis takes it a step further and aims to develop a LiDAR-based 3D object detection model that operates in real-time, with emphasis on autonomous driving scenarios. We propose 3D YOLO, an extension of YOLO (You Only Look Once), which is one of the fastest state-of-the-art 2D object detectors for images. The proposed model takes point cloud data as input and outputs 3D bounding boxes with class scores in real-time. Most of the existing 3D object detectors use hand-crafted features, while our model follows the end-to-end learning fashion, which removes manual feature engineering.

    3D YOLO pipeline consists of two networks: (a) Feature Learning Network, an artificial neural network that transforms the input point cloud to a new feature space; (b) 3DNet, a novel convolutional neural network architecture based on YOLO that learns the shape description of the objects.

    Our experiments on the KITTI dataset shows that the 3D YOLO has high accuracy and outperforms the state-of-the-art LiDAR-based models in efficiency. This makes it a suitable candidate for deployment in autonomous vehicles.

  • 49.
    Alam, Samiul
    KTH, School of Electrical Engineering and Computer Science (EECS).
    Recurrent neural networks in electricity load forecasting2018Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    In this thesis two main studies are conducted to compare the predictive capabilities of feed-forward neural networks (FFNN) and long short-term memory networks (LSTM) in electricity load forecasting.

    The first study compares univariate networks using past electricity load, as well as multivariate networks using past electricity load and air temperature, in day-ahead load forecasting using varying lookback periods and sparsity of past observations. The second study compares FFNNs and LSTMs of different complexities (i.e. network sizes) when restrictions imposed by limitations of the real world are taken into consideration.

    No significant differences are found between the predictive performances of the two neural network approaches. However, adding air temperature as extra input to the LSTM is found to significantly decrease its performance. Furthermore, the predictive performance of the FFNN is found to significantly decrease as the network complexity grows, while the predictive performance of the LSTM is found to increase as the network complexity grows. All the findings considered, we do not find that there is enough evidence in favour of the LSTM in electricity load forecasting.

  • 50.
    Albrecht, Tomás
    KTH, School of Electrical Engineering and Computer Science (EECS), Media Technology and Interaction Design, MID.
    Designing the Publikvitto, a system to make government expenditure tangible2018Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Air transportation is essential to our society. It enables global trading, brings people together, and lets travelers explore distant parts of the world. However, flying is a highly unsustainable behavior and accounts for roughly 2% of all carbon emissions; with industry and research forecasting constant growth in the coming years. The economic benefits rhetoric often prevails over the environmental costs, though; motivating governments to give incentives to airports and airlines. The Swedish Government, despite its green goals and pro-sustainability actions, is no exception, and both municipal and federal funds support the air route network.

    This thesis reports on the development of the Publikvitto, a system designed to help citizen make sense of the government's incentives to the flying industry. The process is based on research through design and inspired by reflective practices. The primary outcome are insights into the relationship between designer, social issues, and government's actions; and how these elements can be approached in order to design artifacts that motivate people to engage in political discussions.

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