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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.
    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)
  • 5.
    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.

  • 6. 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.

  • 7. 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.

  • 8.
    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)
  • 9.
    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.

  • 10.
    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.

  • 11.
    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.

  • 12.
    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.

  • 13.
    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.

  • 14.
    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.

  • 15.
    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.

  • 16.
    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.

  • 17.
    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.

  • 18.
    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%.

  • 19.
    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.

  • 20.
    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.

  • 21.
    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.

  • 22.
    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.

  • 23.
    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.

  • 24.
    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.

  • 25.
    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.

  • 26.
    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.

  • 27.
    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. 

  • 28.
    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.

  • 29.
    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.

  • 30.
    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.

  • 31.
    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.

  • 32.
    Aleksandrauskaite, Ruth
    KTH, School of Electrical Engineering and Computer Science (EECS), Automatic Control.
    Analysis of Velocity Estimation Methods for High-Performance Motion Control Systems2018Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    The majority of all commercial electronics hardware is manufactured usingSurface Mount Technology (SMT). Nevertheless, the increased complexityand miniaturization of electronics impose tough performance requirementson the automation process.The research in this paper concerns test and analysis of alternative velocityestimation methods for high-performance embedded motion control systems.The motion system in Mycronic’s pick and place machines is regulated by amotion controller consisting of a feedforward component and a feedback controller.The linear displacement is measured with an incremental encoder andthe velocity is estimated with a state observer. Previous work suggests thatthe velocity estimation is inadequate.Different observer designs including state and disturbance estimators weretested and evaluated through simulations in MATLAB SIMULINKr. Afterthat, experiments were performed on a conveyor retrieved from a pick andplace machine.The results show that a Kalman filter is the best state estimator. However,the method requires extensive tuning to attain good performance. The trackingperformance and robustness of the motion control system was highly improvedwhen using a Perturbation observer with Kalman filtering. Nonetheless,the settling time for point-to-point movements was somewhat shorterwhen using a Kalman filter alone.

  • 33.
    Alinder, Helena
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS).
    Nilsson, Josefin
    KTH, School of Electrical Engineering and Computer Science (EECS).
    An Evaluation of the Indian Buffet Process as Part of a Recommendation System2018Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

     This report investigates if it is possible to use the Indian Buffet Process (IBP), a stochastic process that defines a probability distribution, as part of a recommendation system. The report focuses on recommendation systems where one type of object, for instance movies, is recommended to another type of object, for instance users.        

    A concept of performing link prediction with IBP is presented, along with a method for performing inference. Three papers that are related to the subject are presented and their results are analyzed together with additional experiments on an implementation of the IBP.       

    The report arrives at the conclusion that it is possible to use IBP in a recommendation system when recommending one object to another. In order to use IBP priors in a recommendation system which include real-life datasets, the paper suggests the use of a coupled version of the IBP model and if possible perform inference with a parallel Gibbs sampling.

  • 34.
    Alizadeh, Mahmoud
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering. Department of Electronics, Mathematics and Natural Sciences, University of Gävle (HiG), Gävle, Sweden.
    Rönnow, D.
    Händel, Peter
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Characterization of Volterra Kernels for RF Power Amplifiers Using a Two-Tone Signal and a Large-Signal2018In: 2018 12th International Conference on Communications, COMM 2018 - Proceedings, Institute of Electrical and Electronics Engineers (IEEE), 2018, p. 351-356, article id 8430119Conference paper (Refereed)
    Abstract [en]

    The 3rd-order Volterra kernels of a radio frequency (RF) power amplifier (PA) are characterized using a large-signal and a two-tone probing-signal. In this technique, the magnitude and phase asymmetries of the kernels of the PA excited by the probing-signal are analyzed in different amplitude regions of the large-signal. The device under test is a class-AB PA operating at 2.14 GHz. The maximum sweeping frequency space of the probing-signal is 20 MHz. The results indicate that the Volterra kernels of the PA show different behaviors (frequency dependency and asymmetry) in different regions.

  • 35.
    Alkeaid, Majed Mohammed G
    KTH, School of Electrical Engineering and Computer Science (EECS), Electric Power and Energy Systems. KTH, School of Industrial Engineering and Management (ITM).
    Study of NEOM city renewable energy mix and balance problem2018Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    It is important for NEOM management in the contemporary world to put in place NEOM projects using the available resources. The region in which the NEOM project is spacious and vast with conditions suited to generate energy from solar and wind. The NEOM projectis expected to be set up in the very resourceful state of Saudi Arabia. The purpose of the study is to assist in setting up a sustainable city through the exploitation of solar and wind energy. The aim of the study was to assist in the generation of more than 10 GW renewable energy to replace approximately 80,000 barrels of fossil energy. The problem of coming up with renewable and sustainable energy from the unexploited sources is addressed. The renewable city is expected to be a technological hub based on Green Energy with 100% renewable energy, which is correspond to 72:4GW. Freiburg and Masdar as renewable cities are used as case studies in the research. NEOM power generation capacity is capable to cover Saudi Arabia power generation capacity (approximately 71GW), which is more than enough for a city. The study reveals that the total power generation from wind farms, tidal farms, solar stations, and solar power tower stations are 9:1373GW, 4:76GW, 57:398GW and 1:11GW respectively. Saudi Arabia has plans to set up 16 nuclear plants (17 GW each) for energy purposes (total of 272 GW), which will be part of Saudi Arabia national grid and will be more than enough to cover NEOM electricity demand in case NEOM does not reach demand capacity. In case NEOM energy does not meet the demand, electricity generation from 16 Nuclearpower plants generating 17GW each, and 6 Natural underground batteries with a capacity of 120MW each are recommended. The study results can be applied in NEOM Institute of Science and Technology for further research on renewable energy. The findings can also be used for research extension of HVDC transmission lines between NEOM and Saudi Arabia main grid, Egypt, and Jordan.

  • 36. Alm, L.
    et al.
    Farrugia, C. J.
    Paulson, K. W.
    Argall, M. R.
    Torbert, R. B.
    Burch, J. L.
    Ergun, R. E.
    Russell, C. T.
    Strangeway, R. J.
    Khotyaintsev, Y. V.
    Lindqvist, Per-Arne
    KTH, School of Electrical Engineering and Computer Science (EECS), Space and Plasma Physics.
    Marklund, Göran
    KTH, School of Electrical Engineering and Computer Science (EECS), Space and Plasma Physics.
    Giles, B. L.
    Differing Properties of Two Ion-Scale Magnetopause Flux Ropes2018In: Journal of Geophysical Research - Space Physics, ISSN 2169-9380, E-ISSN 2169-9402, Vol. 123, no 1, p. 114-131Article in journal (Refereed)
    Abstract [en]

    In this paper, we present results from the Magnetospheric Multiscale constellation encountering two ion-scale, magnetopause flux ropes. The two flux ropes exhibit very different properties and internal structure. In the first flux rope, there are large differences in the currents observed by different satellites, indicating variations occurring over sub-d(i) spatial scales, and time scales on the order of the ion gyroperiod. In addition, there is intense wave activity and particle energization. The interface between the two flux ropes exhibits oblique whistler wave activity. In contrast, the second flux rope is mostly quiescent, exhibiting little activity throughout the encounter. Changes in the magnetic topology and field line connectivity suggest that we are observing flux rope coalescence.

  • 37.
    Almeida, Diogo
    et al.
    KTH, School of Computer Science and Communication (CSC), Robotics, perception and learning, RPL. KTH.
    Ambrus, Rares
    KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP.
    Caccamo, Sergio
    KTH, School of Electrical Engineering and Computer Science (EECS), Robotics, perception and learning, RPL.
    Chen, Xi
    KTH.
    Cruciani, Silvia
    Pinto Basto De Carvalho, Joao F
    KTH, School of Electrical Engineering and Computer Science (EECS), Robotics, perception and learning, RPL.
    Haustein, Joshua
    KTH, School of Electrical Engineering and Computer Science (EECS), Robotics, perception and learning, RPL.
    Marzinotto, Alejandro
    KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP.
    Vina, Francisco
    KTH.
    Karayiannidis, Yannis
    KTH.
    Ögren, Petter
    KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Optimization and Systems Theory.
    Jensfelt, Patric
    KTH, School of Computer Science and Communication (CSC), Robotics, perception and learning, RPL.
    Kragic, Danica
    KTH, School of Computer Science and Communication (CSC), Robotics, perception and learning, RPL.
    Team KTH’s Picking Solution for the Amazon Picking Challenge 20162017In: Warehouse Picking Automation Workshop 2017: Solutions, Experience, Learnings and Outlook of the Amazon Robotics Challenge, 2017Conference paper (Other (popular science, discussion, etc.))
    Abstract [en]

    In this work we summarize the solution developed by Team KTH for the Amazon Picking Challenge 2016 in Leipzig, Germany. The competition simulated a warehouse automation scenario and it was divided in two tasks: a picking task where a robot picks items from a shelf and places them in a tote and a stowing task which is the inverse task where the robot picks items from a tote and places them in a shelf. We describe our approach to the problem starting from a high level overview of our system and later delving into details of our perception pipeline and our strategy for manipulation and grasping. The solution was implemented using a Baxter robot equipped with additional sensors.

  • 38.
    Almeida, Diogo
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Robotics, perception and learning, RPL.
    Karayiannidis, Yiannis
    KTH, School of Electrical Engineering and Computer Science (EECS), Robotics, perception and learning, RPL. Dept. of Electrical Eng., Chalmers University of Technology.
    Cooperative Manipulation and Identification of a 2-DOF Articulated Object by a Dual-Arm Robot2018In: / [ed] IEEE, 2018Conference paper (Refereed)
    Abstract [en]

    In this work, we address the dual-arm manipula-tion of a two degrees-of-freedom articulated object that consistsof two rigid links. This can include a linkage constrainedalong two motion directions, or two objects in contact, wherethe contact imposes motion constraints. We formulate theproblem as a cooperative task, which allows the employment ofcoordinated task space frameworks, thus enabling redundancyexploitation by adjusting how the task is shared by the robotarms. In addition, we propose a method that can estimate thejoint location and the direction of the degrees-of-freedom, basedon the contact forces and the motion constraints imposed bythe object. Experimental results demonstrate the performanceof the system in its ability to estimate the two degrees of freedomindependently or simultaneously.

  • 39.
    Almeida, Diogo
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Robotics, perception and learning, RPL.
    Karayiannidis, Yiannis
    KTH, School of Electrical Engineering and Computer Science (EECS), Robotics, perception and learning, RPL. Chalmers University of Technology.
    Folding Assembly by Means of Dual-Arm Robotic Manipulation2016In: 2016 IEEE International Conference on Robotics and Automation, IEEE conference proceedings, 2016, p. 3987-3993Conference paper (Refereed)
    Abstract [en]

    In this paper, we consider folding assembly as an assembly primitive suitable for dual-arm robotic assembly, that can be integrated in a higher level assembly strategy. The system composed by two pieces in contact is modelled as an articulated object, connected by a prismatic-revolute joint. Different grasping scenarios were considered in order to model the system, and a simple controller based on feedback linearisation is proposed, using force torque measurements to compute the contact point kinematics. The folding assembly controller has been experimentally tested with two sample parts, in order to showcase folding assembly as a viable assembly primitive.

  • 40.
    Almeida, Teresa
    KTH, School of Electrical Engineering and Computer Science (EECS), Media Technology and Interaction Design, MID.
    Designing for Women: Situated Knowledge, Intimate Health and Everyday Life2018Conference paper (Other academic)
  • 41.
    Almeida, Teresa
    KTH, School of Electrical Engineering and Computer Science (EECS), Media Technology and Interaction Design, MID.
    Designing Technologies for Intimate Care in Women2018Conference paper (Other (popular science, discussion, etc.))
  • 42.
    Almeida, Teresa
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS).
    Juul Søndergaard, Marie Louise
    Aarhus University, Denmark.
    Homewood, Sarah
    IT University of Copenhagen, Denmark.
    Morrissey, Kellie
    Open Lab, Newcastle University, England.
    Balaam, Madeline
    KTH, School of Electrical Engineering and Computer Science (EECS), Media Technology and Interaction Design, MID.
    Woman-Centered Design2018Conference paper (Refereed)
    Abstract [en]

    This Conversation seeks to examine woman-centered design as a novel form of inquiry in design research practice. Drawing on the ‘woman-centered approach’ put forward in (Almeida 2017), this Conversation contributes to discussions on the intersection of feminism(s), gender and design research. In the Conversation we will explore how design of technologies and interactions can act critically in the ways that they serve, refigure and redefine women’s bodies in light of what woman is. Through analyzing design artefacts, we will discuss what impact the understandings of woman have in the design of technology and interventions. Through making as a catalyst for discussion, we will explore how these understandings can contribute to inform the design of technologies for women. As suggested by Judith Butler, “what’s a woman is a question that should remain open” (Kotz and Bankowsky 1992), and we aim to facilitate an open Conversation about the challenges and opportunities of designing for and with woman, which will support the development of a conceptual framework for a woman-centered design methodology.

  • 43.
    Almosawi, Massar
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS).
    Djupsjö, Kristoffer
    KTH, School of Electrical Engineering and Computer Science (EECS).
    IoT Security Applied on a Smart Door Lock Application2018Independent thesis Basic level (professional degree), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    This thesis describes the development of an IOT application based upon Digitizing a smart door lock for making it connected to the internet and able to recognize employees that work in the office.

    This thesis concentrates primarily on the security aspects by listing the typical security challenges in IOT systems in general and summing these challenges up to develop a functional and secure product from scratch. A microcontroller is chosen for this project and a test environment is built to experiment and develop the security breaches. Architectural designs are chosen for the API being developed and even for the Android Application. A detailed description is made of the multi-master database represented by Azure active directory and its importance to achieving the security of an essential security breach. A new technique called Eddystone is introduced in the project to serve the transmission protocol with Bluetooth beacons.

    The final stage of this project is completing the development of the Android application and making sure that all the subsystems developed do communicate with each other, to deliver a functional and secure flow of the IoT system.

  • 44.
    Al-qaysi, Ibrahim
    KTH, School of Electrical Engineering and Computer Science (EECS).
    Communicating with a Smart Pillbox via Near Field Communication (NFC): A Mobile Application for Healthcare Professionals2018Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    The lack of medication adherence leads to an incremental risk of diseases which can be a major burden on the individual, healthcare system, and society. Hence, healthcare professionals have a central role and should manage, guide, educate, and make their patient more involved in their treatment and thereby promoting a better medication adherence.

    Medication adherence is a great challenge for many patients with chronic conditions, elderly patient, or patient prescribed to long-term medication. The rapid development and deployment of mobile phones in the healthcare industry has an important role to play in this area and has led to the development of new phone features and applications that can help both caregivers and patients with managing and monitoring medication intakes. This development and support of mobile phones and applications have created and improved doctor-patient interaction.

    Today, there is no easy way for healthcare professionals to monitor and help patients with their medication intakes. A solution to this problem is to develop a mobile application that communicates with a smart pillbox via near field communication (NFC) to monitor, manage, and improve patient’s medication intakes in an easy and accessible manner. Using NFC as a communication technology allows data to be wirelessly transferred from phone to pillbox and vice versa. This solution will help healthcare professionals to create better treatment conditions and fewer side effects for their patients. These patients will be more knowledgeable and motivated to take greater responsibility in following doctor’s instructions, thereby improving their treatment process.

    The application is tested and evaluated during every iteration phase of the development process. These tests have been conducted by allowing healthcare professionals to test the application and provide feedback on their experience when using the app. Conducting these tests have helped with generating new ideas, features, and functionalities, but also helped to improve the user interface to make the application as user-friendly as possible.

  • 45.
    Alsing, Oscar
    KTH, School of Electrical Engineering and Computer Science (EECS).
    Mobile Object Detection using TensorFlow Lite and Transfer Learning2018Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    With the advancement in deep learning in the past few years, we are able to create complex machine learning models for detecting objects in images, regardless of the characteristics of the objects to be detected. This development has enabled engineers to replace existing heuristics-based systems in favour of machine learning models with superior performance. In this report, we evaluate the viability of using deep learning models for object detection in real-time video feeds on mobile devices in terms of object detection performance and inference delay as either an end-to-end system or feature extractor for existing algorithms. Our results show a significant increase in object detection performance in comparison to existing algorithms with the use of transfer learning on neural networks adapted for mobile use.

  • 46.
    Al-Tai, Elias
    KTH, School of Electrical Engineering and Computer Science (EECS).
    An evaluation of the expressive power and performance of JSON-to-JSON transformation languages2018Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    JSON-to-JSON transformation languages enable the transformation of a JSON document into another JSON document. As JSON is gradually becoming the most used interchange format on the Internet there is a need for transformation languages that can transform the data stored in JSON in order for the data to be used with other systems. The transformation can transform the document structurally, for example by altering the hierarchical structure of the document. The transformation can also transform the document textually, for example by renaming fields or altering values. None of the existing JSON-to-JSON transformation languages have become a standard (Jellife, 2017). This work evaluates the expressive power of the JSON-to-JSON transformation language Jolt. Jolt have recently been adopted by Apache and support have been introduced in some of their products. If a transformation language have expressive power that are at least equal to Nested Relational Algebra this implies that a transformation language can perform many advanced transformations. In this work  a formal model of Jolt is defined, referred to as Jolt0, in order to compare its expressive powers to Nested Relational Algebra. For that purpose, the operations of another formal model called MQuery which have been proven to have equivalent expressive power to Nested Relational Algebra are translated into Jolt0. It is shown that Jolt does not have expressive powers equivalent to Nested Relational Algebra.

    We further compared the performance of four JSON-to-JSON transformation languages (Jolt, Handlebars, Liquid, and XSLT 3.0) by constructing tests where the different transformation languages executed equivalent transformations. The transformations were evaluated by measuring runtime and memory usage. The study shows that XSLT 3.0 performed worst in all run time and memory usage tests. When transforming large input data XSLT 3.0 performed significantly worse than the other languages.

  • 47. Ambrazaitis, G.
    et al.
    House, David
    KTH, School of Electrical Engineering and Computer Science (EECS), Speech, Music and Hearing, TMH.
    Multimodal prominences: Exploring the patterning and usage of focal pitch accents, head beats and eyebrow beats in Swedish television news readings2017In: Speech Communication, ISSN 0167-6393, E-ISSN 1872-7182, Vol. 95, p. 100-113Article in journal (Refereed)
    Abstract [en]

    Facial beat gestures align with pitch accents in speech, functioning as visual prominence markers. However, it is not yet well understood whether and how gestures and pitch accents might be combined to create different types of multimodal prominence, and how specifically visual prominence cues are used in spoken communication. In this study, we explore the use and possible interaction of eyebrow (EB) and head (HB) beats with so-called focal pitch accents (FA) in a corpus of 31 brief news readings from Swedish television (four news anchors, 986 words in total), focusing on effects of position in text, information structure as well as speaker expressivity. Results reveal an inventory of four primary (combinations of) prominence markers in the corpus: FA+HB+EB, FA+HB, FA only (i.e., no gesture), and HB only, implying that eyebrow beats tend to occur only in combination with the other two markers. In addition, head beats occur significantly more frequently in the second than in the first part of a news reading. A functional analysis of the data suggests that the distribution of head beats might to some degree be governed by information structure, as the text-initial clause often defines a common ground or presents the theme of the news story. In the rheme part of the news story, FA, HB, and FA+HB are all common prominence markers. The choice between them is subject to variation which we suggest might represent a degree of freedom for the speaker to use the markers expressively. A second main observation concerns eyebrow beats, which seem to be used mainly as a kind of intensification marker for highlighting not only contrast, but also value, magnitude, or emotionally loaded words; it is applicable in any position in a text. We thus observe largely different patterns of occurrence and usage of head beats on the one hand and eyebrow beats on the other, suggesting that the two represent two separate modalities of visual prominence cuing.

  • 48.
    Anadon Leon, Hector
    KTH, School of Electrical Engineering and Computer Science (EECS).
    3D Shape Detection for Augmented Reality2018Independent thesis Advanced level (professional degree), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    In previous work, 2D object recognition has shown exceptional results. However, it is not possible to sense the environment spatial information, where the objects are and what they are. Having this knowledge could imply improvements in several fields like Augmented Reality by allowing virtual characters to interact more realistically with the environment and Autonomous cars by being able to make better decisions knowing where the objects are in a 3D space.

    The proposed work shows that it is possible to predict 3D bounding boxes with semantic labels for 3D object detection and a set of primitives for 3D shape recognition from multiple objects in a indoors scene using an algorithm that receives as input an RGB image and its 3D information. It uses Deep Neural Networks with novel architectures for point cloud feature extraction. It uses a unique feature vector capable of representing the latent space of the object that models its shape, position, size and orientation for multi-task prediction trained end-to-end with unbalanced datasets. It runs in real time (5 frames per second) in a live video feed.

    The method is evaluated in the NYU Depth Dataset V2 using Average Precision for object detection and 3D Intersection over Union and surface-to-surface distance for 3D shape. The results confirm that it is possible to use a shared feature vector for more than one prediction task and it generalizes for unseen objects during the training process achieving state-of-the-art results for 3D object detection and 3D shape prediction for the NYU Depth Dataset V2. Qualitative results are shown in real particular captured data showing that there could be navigation in a real-world indoor environment and that there could be collisions between the animations and the detected objects improving the interaction character-environment in Augmented Reality applications.

  • 49.
    Andersson López, Lisa
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS).
    Lallerstedt Blomqvist, Siri
    KTH, School of Electrical Engineering and Computer Science (EECS).
    Källkritik i en värld av ansiktsanimering och talmanipulation2018Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    Recent software innovations have made it easy to manipulate video and voice recordings. Thus the intentions, the software could easily be misused and become a powerful tool for those who deliberately tries to misinform the public through manipulated information. As the manipulated information become more sophisticated, the demands on the journalists’ ability to tell real representations from manipulated will increase.

    This study explores how prepared some of the leading Swedish news outlets are for the advancing technology. Through semi structured interviews have experts in the field expressed what kind of resources the journalists need to detect manipulated sources, and then have three editorial offices responded whether they possess or are prepared to acquire such tools and competence. The conclusion is that the targeted news outlets did not have the full capability to detect both manipulated video and voice recordings in-house at the time the study was made.

  • 50.
    Andersson, Morgan
    KTH, School of Electrical Engineering and Computer Science (EECS).
    Personal news video recommendations based on implicit feedback: An evaluation of different recommender systems with sparse data2018Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    The amount of video content online will nearly triple in quantity by 2021 compared to 2016. The implementation of sophisticated filters is of paramount importance to manage this information flow. The research question of this thesis asks to what extent it is possible to generate personal recommendations, based on the data that news videos implies. The objective is to evaluate how different recommender systems compare to complete random, each other and how they are received by users in a test environment.

    This study was performed during the spring of 2018, and explore four different algorithms. These recommender systems include a content-based, a collaborative-filter, a hybrid model and a popularity model as a baseline. The dataset originates from a news media startup called Newstag, who provide video news on a global scale. The data is sparse and includes implicit feedback only.

    Three offline experiments and a user test were performed. The metric that guided the algorithms offline performance was their recall at 5 and 10, due to the fact that the top list of recommended items are of most interest. A comparison was done on different amounts of meta-data included during training. Another test explored respective algorithms performance as the density of the data increased. In the user test, a mean opinion score was calculated based on the quality of recommendations that each of the algorithms generated for the test subjects. The user test also included randomly sampled news videos to compare with as a baseline.

    The results indicate that for this specific setting and data set, the content-based recommender system performed best in both the recall at five and ten, as well as in the user test. All of the algorithms outperformed the random baseline.

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