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  • 1.
    A Elhassan, Amro
    KTH, School of Electrical Engineering (EES).
    Building automation and control2012Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
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  • 2.
    A, Fredrik
    et al.
    KTH, School of Electrical Engineering (EES).
    Forsberg, A
    KTH, School of Electrical Engineering (EES).
    Forsén, Tobias
    KTH, School of Electrical Engineering (EES).
    Tracking Using Wireless Camera Networks2015Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
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  • 3.
    A. M. Naiini, Maziar
    KTH, School of Information and Communication Technology (ICT), Integrated Devices and Circuits.
    Horizontal Slot Waveguides for Silicon Photonics Back-End Integration2014Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    This thesis presents the development of integrated silicon photonic devices. These devices are compatible with the present and near future CMOS technology. High-khorizontal grating couplers and waveguides are proposed. This work consists of simulations and device design, as well as the layout for the fabrication process, device fabrication, process development, characterization instrument development and electro-optical characterizations.

    The work demonstrates an alternative solution to costly silicon-on-insulator photonics. The proposed solution uses bulk silicon wafers and thin film deposited waveguides. Back-end deposited horizontal slot grating couplers and waveguides are realized by multi-layers of amorphous silicon and high-k materials.

    The achievements of this work include: A theoretical study of fully etched slot grating couplers with Al2O3, HfO2 and AIN, an optical study of the high-k films with spectroscopic ellipsometry, an experimental demonstration of fully etched SiO2 single slot grating couplers and double slot Al2O3 grating couplers, a practical demonstration of horizontal double slot high-k waveguides, partially etched Al2O3 single slot grating couplers, a study of a scheme for integration of the double slot Al2O3  waveguides with selectively grown germanium PIN photodetectors, realization of test chips for the integrated germanium photodetectors, and study of integration with graphene photodetectors through embedding the graphene into a high-k slot layer.

    From an application point of view, these high-k slot waveguides add more functionality to the current silicon photonics. The presented devices can be used for low cost photonics applications. Also alternative optical materials can be used in the context of this photonics platform.

    With the robust design, the grating couplers result in improved yield and a more cost effective solution is realized for integration of the waveguides with the germanium and graphene photodetectors.

     

     

     

     

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    Thesis
  • 4.
    A. Mouris, Boules
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Information Science and Engineering.
    Ghauch, Hadi
    Department of COMELEC, Institut Mines-Telecom, Telecom-ParisTech, Paris, 91120, France.
    Thobaben, Ragnar
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Information Science and Engineering.
    Jonsson, B. Lars G.
    KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electromagnetic Engineering.
    Multi-tone Signal Optimization for Wireless Power Transfer in the Presence of Wireless Communication Links2020In: IEEE Transactions on Wireless Communications, ISSN 1536-1276, E-ISSN 1558-2248, Vol. 19, no 5, p. 3575-3590Article in journal (Refereed)
    Abstract [en]

    In this paper, we study optimization of multi-tone signals for wireless power transfer (WPT) systems. We investigate different non-linear energy harvesting models. Two of them are adopted to optimize the multi-tone signal according to the channel state information available at the transmitter. We show that a second-order polynomial curve-fitting model can be utilized to optimize the multi-tone signal for any RF energy harvester design. We consider both single-antenna and multi-antenna WPT systems. In-band co-existing communication links are also considered in this work by imposing a constraint on the received power at the nearby information receiver to prevent its RF front end from saturation. We emphasize the importance of imposing such constraint by explaining how inter-modulation products, due to saturation, can cause high interference at the information receiver in the case of multi-tone signals. The multi-tone optimization problem is formulated as a non-convex linearly constrained quadratic program. Two globally optimal solution approaches using mixed-integer linear programming and finite branch-and-bound techniques are proposed to solve the problem. The achieved improvement resulting from applying both solution methods to the multi-tone optimization problem is highlighted through simulations and comparisons with other solutions existing in the literature.

  • 5.
    A. Mouris, Boules
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Information Science and Engineering.
    Kolitsidas, Christos
    Ericsson, Systems and Technology-HW Research, Kista, 164 80, Sweden.
    Thobaben, Ragnar
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Information Science and Engineering.
    A Dual-Polarized Multi-Antenna Structure for Simultaneous Transmission of Wireless Information and Power2019In: 2019 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, APSURSI 2019 - Proceedings, IEEE, 2019, p. 1805-1806, article id 8889079Conference paper (Refereed)
    Abstract [en]

    In this paper, a dual-polarized multi-antenna structure is designed at 2.45 GHz with the goal of allowing simultaneous transmission of wireless information and power. Differential feeding was used to minimize the mutual coupling due to radiation leakage in addition to a mushroom-type EBG structure for suppressing the surface waves. Simulation results for the proposed structure show a mutual coupling level lower than -40 dB between the information transmitting antenna and the power transmitting antennas for both polarizations. The isolation level between the antennas is improved by at least 22 dB and 14 dB for the E-plane and H-plane coupling, respectively.

  • 6.
    Aagaard Fransson, Erik Johannes
    et al.
    KTH, School of Electrical Engineering (EES), Electromagnetic Engineering.
    Wall-Horgen, Tobias
    KTH, School of Electrical Engineering (EES), Electromagnetic Engineering.
    Building and Evaluating a 3D Scanning System for Measurementsand Estimation of Antennas and Propagation Channels2012Independent thesis Advanced level (professional degree), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Wireless communications rely, among other things, on theunderstanding of the properties of the radio propagationchannel, the antennas and their interplay. Adequate measurementsare required to verify theoretical models and togain knowledge of the channel behavior and antenna performance.As a result of this master thesis we built a 3D fieldscanner measurement system to predict multipath propagationand to measure antenna characteristics. The 3Dscanner allows measuring a signal at the point of interestalong a line, on a surface or within a volume in space. In orderto evaluate the system, we have performed narrowbandchannel sounding measurements of the spatial distributionof waves impinging at an imaginary spherical sector. Datawas used to estimate the Angle-of-Arrivals (AoA) and amplitudeof the waves. An estimation method is presented tosolve the resulting inverse problem by means of regularizationwith truncated singular value decomposition. The regularizedsolution was then further improved with the helpof a successive interference cancellation algorithm. Beforeapplying the method to measurement data, it was testedon synthetic data to evaluate its performance as a functionof the noise level and the number of impinging waves. Inorder to minimize estimation errors it was also required tofind the phase center of the horn antenna used in the channelmeasurements. The task was accomplished by directmeasurements and by the regularization method, both resultsbeing in good agreement.

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  • 7.
    Aarno, Daniel
    et al.
    KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP. KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS.
    Ekvall, Staffan
    KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP. KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS.
    Kragic, Danica
    KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP. KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS.
    Adaptive virtual fixtures for machine-assisted teleoperation tasks2005In: 2005 IEEE International Conference on Robotics and Automation (ICRA), Vols 1-4, 2005, p. 1139-1144Conference paper (Refereed)
    Abstract [en]

    It has been demonstrated in a number of robotic areas how the use of virtual fixtures improves task performance both in terms of execution time and overall precision, [1]. However, the fixtures are typically inflexible, resulting in a degraded performance in cases of unexpected obstacles or incorrect fixture models. In this paper, we propose the use of adaptive virtual fixtures that enable us to cope with the above problems. A teleoperative or human machine collaborative setting is assumed with the core idea of dividing the task, that the operator is executing, into several subtasks. The operator may remain in each of these subtasks as long as necessary and switch freely between them. Hence, rather than executing a predefined plan, the operator has the ability to avoid unforeseen obstacles and deviate from the model. In our system, the probability that the user is following a certain trajectory (subtask) is estimated and used to automatically adjusts the compliance. Thus, an on-line decision of how to fixture the movement is provided.

  • 8.
    Aarno, Daniel
    et al.
    KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS. KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP.
    Kragic, Danica
    KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS. KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP.
    Layered HMM for motion intention recognition2006In: 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems, Vols 1-12, NEW YORK: IEEE , 2006, p. 5130-5135Conference paper (Refereed)
    Abstract [en]

    Acquiring, representing and modeling human skins is one of the key research areas in teleoperation, programming. by-demonstration and human-machine collaborative settings. One of the common approaches is to divide the task that the operator is executing into several subtasks in order to provide manageable modeling. In this paper we consider the use of a Layered Hidden Markov Model (LHMM) to model human skills. We evaluate a gestem classifier that classifies motions into basic action-primitives, or gestems. The gestem classifiers are then used in a LHMM to model a simulated teleoperated task. We investigate the online and offline classilication performance with respect to noise, number of gestems, type of HAIM and the available number of training sequences. We also apply the LHMM to data recorded during the execution of a trajectory-tracking task in 2D and 3D with a robotic manipulator in order to give qualitative as well as quantitative results for the proposed approach. The results indicate that the LHMM is suitable for modeling teleoperative trajectory-tracking tasks and that the difference in classification performance between one and multi dimensional HMMs for gestem classification is small. It can also be seen that the LHMM is robust w.r.t misclassifications in the underlying gestem classifiers.

  • 9. Aarts, Mark
    et al.
    Reiser, Alain
    Laboratory for Nanometallurgy, ETH Zürich, Department of Materials, Vladimir-Prelog-Weg 1-5/10, Zürich, Switzerland.
    Spolenak, Ralph
    Alarcon-Llado, Esther
    Confined pulsed diffuse layer charging for nanoscale electrodeposition with an STM2022In: Nanoscale Advances, ISSN 25160230, Vol. 4, no 4, p. 1182-1190Article in journal (Refereed)
  • 10.
    Abad Caballero, Israel Manuel
    KTH, School of Information and Communication Technology (ICT), Microelectronics and Information Technology, IMIT.
    Secure Mobile Voice over IP2003Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Voice over IP (VoIP) can be defined as the ability to make phone calls and to send faxes (i.e., to do everything we can do today with the Public Switched Telephone Network, PSTN) over IP−based data networks with a suitable quality of service and potentially a superior cost/benefit ratio. There is a desire to provide (VoIP) with the suitable security without effecting the performance of this technology. This becomes even more important when VoIP utilizes wireless technologies as the data networks (such as Wireless Local Area Networks, WLAN), given the bandwidth and other constraints of wireless environments, and the data processing costs of the security mechanisms. As for many other (secure) applications, we should consider the security in Mobile VoIP as a chain, where every link, from the secure establishment to the secure termination of a call, must be secure in order to maintain the security of the entire process.

    This document presents a solution to these issues, providing a secure model for Mobile VoIP that minimizes the processing costs and the bandwidth consumption. This is mainly achieved by making use of high− throughput, low packet expansion security protocols (such as the Secure Real−Time Protocol, SRTP); and high−speed encryption algorithms (such as the Advanced Encryption Standard, AES).

    In the thesis I describe in detail the problem and its alternative solutions. I also describe in detail the selected solution and the protocols and mechanisms this solution utilizes, such as the Transport Layer Security (TLS) for securing the Session Initiation Protocol (SIP), the Real−Time Protocol (RTP) profile Secure Real−Time Protocol (SRTP) for securing the media data transport , and the Multimedia Internet KEYing (MIKEY) as the key−management protocol. Moreover, an implementation of SRTP, called MINIsrtp, is also provided. The oral presentation will provide an overview of these topics, with an in depth examination of those parts which were the most significant or unexpectedly difficult.

    Regarding my implementation, evaluation, and testing of the model, this project in mainly focused on the security for the media stream (SRTP). However, thorough theoretical work has also been performed and will be presented, which includes other aspects, such as the establishment and termination of the call (using SIP) and the key−management protocol (MIKEY).

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  • 11.
    Abad Camarero, Daniel
    KTH, School of Electrical Engineering (EES), Communication Networks.
    Performance analysis of IPv4 / IPv6 protocols over the third generation mobile network2014Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Currently, the IPv4 protocol is heavily used by institutions, companies and individuals, but every day there is a higher number of devices connected to the network such as home appliances, mobile phones or tablets. Each machine or device needs to have its own IP address to communicate with other machines connected to Internet. This implies the need for multiple IP addresses for a single user and the current protocol begins to show some deficiencies due to IPv4 address space exhaustion. Therefore, for several years experts have been working on an IP protocol update: the IPv6 128-bit version can address up to about 340 quadrillion system devices concurrently. With IPv6, today, every person on the planet could have millions of devices simultaneously connected to the Internet.

    The choice of the IP protocol version affects the performance of the UMTS mobile network and the browsers as well. The aim of the project is to measure how the IPv6 protocol performs compared to the previous IPv4 protocol. It is expected that the IPv6 protocol generates a smaller amount of signalling and less time is required to fully load a web page. We have analysed some KPIs (IP data, signalling, web load time and battery) in lab environment using Smartphones, to observe the behaviour of both, the network and the device.  The main conclusion of the thesis is that IPv6 really behaves as expected and generates savings in signalling, although the IP data generated is larger due to the size of the headers. However, there is still much work as only the most important webpages and the applications with a high level of market penetration operate well over the IPv6 protocol.

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    Performance Analysis of IPv4-IPv6 protocols over the Third Generation Mobile Network-Daniel Abad
  • 12.
    Abad Garcia, Carlos
    KTH, School of Electrical Engineering and Computer Science (EECS).
    Error Injection Study for a SpaceFibre In-Orbit Demonstrator2020Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    The space electronics sector is shifting towards the New-Space paradigm, in which traditional space-quali_ed and expensive components and payloads are replaced by commercial o_-the-shelf (COTS) alternatives. This change in mentality is accompanied by the development of inexpensive cubesats, lowering the entry barrie in terms of cost, enabling an increase in scienti_c research in space. However, also well-established and resourceful spacecraft manufacturers are adopting this trend that allows them to become more competitive in the market. Following this trend, Thales Alenia Space is developing R&D activities using COTS components. One example is the SpaceFibre In-Orbit Demonstrator, a digital board integrated in a cubesat payload that aims to test two Intellectual Property blocks implementing the new ECSS standard for high-speed onboard communication. This thesis presents the necessary steps that were taken to integrate the _rmware for the demonstrator's Field-Programmable Gate Array (FPGA) that constitutes the main processing and control unit for the board. The activity is centered around the development of a Leon3 System-on-Chip in VHDL used to manage the components in the board and test the SpaceFibre technology. Moreover, it also addresses the main problem of using COTS components in the space environment: their sensitivity to radiation, that, for a FPGA results in Single-Event Upsets causing the implementation to malfunction, and a potential failure of the mission if they are not addressed. To accomplish the task, a SEU-emulation methodology based in partial recon_guration and integrating the state of the art techniques is elaborated and applied to test the reliability of the SpaceFibre technology. Finally, results show that the mean time between failures of the SpaceFibre Intellectual Property Block using a COTS FPGA is of 170 days for Low Earth Orbit (LEO) and 2278 days for Geostationary Orbit (GEO) if con_guration memory scrubbing is included in the design, enabling its usage in short LEO missions for data transmission. Moreover, tailored mitigation techniques based on the information gathered from applying the proposed methodology are presented to improve the gures. 

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  • 13. Abadal, Sergi
    et al.
    Alarcon, Eduard
    Cabellos-Aparicio, Albert
    Lemme, Max C.
    KTH, School of Information and Communication Technology (ICT), Integrated Devices and Circuits.
    Nemirovsky, Mario
    Graphene-Enabled Wireless Communication for Massive Multicore Architectures2013In: IEEE Communications Magazine, ISSN 0163-6804, E-ISSN 1558-1896, Vol. 51, no 11, p. 137-143Article in journal (Refereed)
    Abstract [en]

    Current trends in microprocessor architecture design are leading towards a dramatic increase of core-level parallelization, wherein a given number of independent processors or cores are interconnected. Since the main bottleneck is foreseen to migrate from computation to communication, efficient and scalable means of inter-core communication are crucial for guaranteeing steady performance improvements in many-core processors. As the number of cores grows, it remains unclear whether initial proposals, such as the Network-on-Chip (NoC) paradigm, will meet the stringent requirements of this scenario. This position paper presents a new research area where massive multicore architectures have wireless communication capabilities at the core level. This goal is feasible by using graphene-based planar antennas, which can radiate signals at the Terahertz band while utilizing lower chip area than its metallic counterparts. To the best of our knowledge, this is the first work that discusses the utilization of graphene-enabled wireless communication for massive multicore processors. Such wireless systems enable broadcasting, multicasting, all-to-all communication, as well as significantly reduce many of the issues present in massively multicore environments, such as data coherency, consistency, synchronization and communication problems. Several open research challenges are pointed out related to implementation, communications and multicore architectures, which pave the way for future research in this multidisciplinary area.

  • 14.
    Abarghouyi, Hadis
    et al.
    IUST, Sch Elect Engn, Tehran 1665973561, Iran.;MTNi Co, Tehran 1665973561, Iran..
    Razavizadeh, S. Mohammad
    IUST, Sch Elect Engn, Tehran 1684613114, Iran..
    Björnson, Emil
    Linköping Univ, Dept Elect Engn ISY, S-58183 Linköping, Sweden..
    QoE-Aware Beamforming Design for Massive MIMO Heterogeneous Networks2018In: IEEE Transactions on Vehicular Technology, ISSN 0018-9545, E-ISSN 1939-9359, Vol. 67, no 9, p. 8315-8323Article in journal (Refereed)
    Abstract [en]

    One of the main goals of the future wireless networks is improving the users' quality of experience (QoE). In this paper, we consider the problem of the QoE-based resource allocation in the downlink of a massive multiple-input multiple-output heterogeneous network. The network consists of a macrocell with a number of small cells embedded in it. The small cells' base stations (BSs) are equipped with a few antennas, while the macro BS is equipped with a massive number of antennas. We consider the two services Video and Web Browsing and design the beamforming vectors at the BSs. The objective is to maximize the aggregated mean opinion score (MOS) of the users under constraints on the BSs' powers and the required quality of service of the users. We also consider extra constraints on the QoE of users to more strongly enforce the QoE in the beamforming design. To reduce the complexity of the optimization problem, we suggest suboptimal and computationally efficient solutions. Our results illustrate that increasing the number of antennas at the BSs and also increasing the number of small cells' antennas in the network leads to a higher user satisfaction.

  • 15. Abasahl, B.
    et al.
    Zand, I.
    Lerma Arce, C.
    Kumar, S.
    Quack, N.
    Jezzini, M. A.
    Hwang, H. Y.
    Gylfason, Kristinn B.
    KTH, School of Electrical Engineering (EES), Micro and Nanosystems.
    Porcel, M. A. G.
    Bogaerts, W.
    Towards Low-Power Reconfigurable Photonic ICs Based on MEMS Technology2018Conference paper (Other academic)
    Abstract [en]

    With the progress and industrialization of photonic integrated circuits (PIC) in the past few decades, there is a strong urge towards design and prototyping in a fast, low-cost and reliable manner. In electronics, this demand is met through field programmable gate arrays (FPGA). In the Horizon 2020 MORPHIC (MEMS-based zerO-power Reconfigurable Photonic ICs) project, we are developing a reconfigurable PIC platform to address this demand in the field of photonics and to facilitate the path from idea towards realization for PIC designers and manufacturers.

  • 16.
    Abbas, Naeem
    KTH, School of Information and Communication Technology (ICT), Electronic, Computer and Software Systems, ECS.
    Runtime Parallelisation Switching for MPEG4 Encoder on MPSoC2008Independent thesis Advanced level (degree of Master (Two Years)), 80 credits / 120 HE creditsStudent thesis
    Abstract [en]

    The recent development for multimedia applications on mobile terminals raised the need for flexible and scalable computing platforms that are capable of providing considerable (application specific) computational performance within a low cost and a low energy budget. The MPSoC with multi-disciplinary approach, resolving application mapping, platform architecture and runtime management issues, provides such multiple heterogeneous, flexible processing elements. In MPSoC, the run-time manager takes the design time exploration information as an input and selects an active Pareto point based on quality requirement and available platform resources, where a Pareto point corresponds to a particular parallelization possibility of target application. To use system’s scalability at best and enhance application’s flexibility a step further, the resource management and Pareto point selection decisions need to be adjustable at run-time. This thesis work experiments run-time Pareto point switching for MPEG-4 encoder. The work involves design time exploration and then embedding of two parallelization possibilities of MPEG-4 encoder into one single component and enabling run-time switching between parallelizations, to give run-time control over adjusting performance-cost criteria and allocation de-allocation of hardware resources at run-time. The newer system has the capability to encode each video frame with different parallelization. The obtained results offer a number of operating points on Pareto curve in between the previous ones at sequence encoding level. The run-time manager can improve application performance up to 50% or can save memory bandwidth up to 15%, according to quality request.

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  • 17.
    Abbas, Zainab
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Software and Computer systems, SCS.
    Scalable Streaming Graph and Time Series Analysis Using Partitioning and Machine Learning2021Doctoral thesis, monograph (Other academic)
    Abstract [en]

    Recent years have witnessed a massive increase in the amount of data generated by the Internet of Things (IoT) and social media. Processing huge amounts of this data poses non-trivial challenges in terms of the hardware and performance requirements of modern-day applications. The data we are dealing with today is of massive scale, high intensity and comes in various forms. MapReduce was a popular and clever choice of handling big data using a distributed programming model, which made the processing of huge volumes of data possible using clusters of commodity machines. However, MapReduce was not a good fit for performing complex tasks, such as graph processing, iterative programs and machine learning. Modern data processing frameworks, that are being popularly used to process complex data and perform complex analysis tasks, overcome the shortcomings of MapReduce. Some of these popular frameworks include Apache Spark for batch and stream processing, Apache Flink for stream processing and Tensor Flow for machine learning.

    In this thesis, we deal with complex analytics on data modeled as time series, graphs and streams. Time series are commonly used to represent temporal data generated by IoT sensors. Analysing and forecasting time series, i.e. extracting useful characteristics and statistics of data and predicting data, is useful for many fields that include, neuro-physiology, economics, environmental studies, transportation, etc. Another useful data representation we work with, are graphs. Graphs are complex data structures used to represent relational data in the form of vertices and edges. Graphs are present in various application domains, such as recommendation systems, road traffic analytics, web analysis, social media analysis. Due to the increasing size of graph data, a single machine is often not sufficient to process the complete graph. Therefore, the computation, as well as the data, must be distributed. Graph partitioning, the process of dividing graphs into subgraphs, is an essential step in distributed graph processing of large scale graphs because it enables parallel and distributed processing.

    The majority of data generated from IoT and social media originates as a continuous stream, such as series of events from a social media network, time series generated from sensors, financial transactions, etc. The stream processing paradigm refers to the processing of data streaming that is continuous and possibly unbounded. Combining both graphs and streams leads to an interesting and rather challenging domain of streaming graph analytics. Graph streams refer to data that is modelled as a stream of edges or vertices with adjacency lists representing relations between entities of continuously evolving data generated by a single or multiple data sources. Streaming graph analytics is an emerging research field with great potential due to its capabilities of processing large graph streams with limited amounts of memory and low latency. 

    In this dissertation, we present graph partitioning techniques for scalable streaming graph and time series analysis. First, we present and evaluate the use of data partitioning to enable data parallelism in order to address the challenge of scale in large spatial time series forecasting. We propose a graph partitioning technique for large scale spatial time series forecasting of road traffic as a use-case. Our experimental results on traffic density prediction for real-world sensor dataset using Long Short-Term Memory Neural Networks show that the partitioning-based models take 12x lower training time when run in parallel compared to the unpartitioned model of the entire road infrastructure. Furthermore, the partitioning-based models have 2x lower prediction error (RMSE) compared to the entire road model. Second, we showcase the practical usefulness of streaming graph analytics for large spatial time series analysis with the real-world task of traffic jam detection and reduction. We propose to apply streaming graph analytics by performing useful analytics on traffic data stream at scale with high throughput and low latency. Third, we study, evaluate, and compare the existing state-of-the-art streaming graph partitioning algorithms. We propose a uniform analysis framework built using Apache Flink to evaluate and compare partitioning features and characteristics of streaming graph partitioning methods. Finally, we present GCNSplit, a novel ML-driven streaming graph partitioning solution, that uses a small and constant in-memory state (bounded state) to partition (possibly unbounded) graph streams. Our results demonstrate that \ours provides high-throughput partitioning and can leverage data parallelism to sustain input rates of 100K edges/s. GCNSplit exhibits a partitioning quality, in terms of graph cuts and load balance, that matches that of the state-of-the-art HDRF (High Degree Replicated First) algorithm while storing three orders of magnitude smaller partitioning state.

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  • 18.
    Abbas, Zainab
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Software and Computer systems, SCS.
    Ivarsson, Jón Reginbald
    KTH.
    Al-Shishtawy, A.
    Vlassov, Vladimir
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Software and Computer systems, SCS.
    Scaling Deep Learning Models for Large Spatial Time-Series Forecasting:
    2019In: Proceedings - 2019 IEEE International Conference on Big Data, Big Data 2019:
    , Institute of Electrical and Electronics Engineers Inc. , 2019, p. 1587-1594
    Conference paper (Refereed)
    Abstract [en]

    Neural networks are used for different machine learning tasks, such as spatial time-series forecasting. Accurate modelling of a large and complex system requires large datasets to train a deep neural network that causes a challenge of scale as training the network and serving the model are computationally and memory intensive. One example of a complex system that produces a large number of spatial time-series is a large road sensor infrastructure deployed for traffic monitoring. The goal of this work is twofold: 1) To model large amount of spatial time-series from road sensors; 2) To address the scalability problem in a real-life task of large-scale road traffic prediction which is an important part of an Intelligent Transportation System.We propose a partitioning technique to tackle the scalability problem that enables parallelism in both training and prediction: 1) We represent the sensor system as a directed weighted graph based on the road structure, which reflects dependencies between sensor readings, and weighted by sensor readings and inter-sensor distances; 2) We propose an algorithm to automatically partition the graph taking into account dependencies between spatial time-series from sensors; 3) We use the generated sensor graph partitions to train a prediction model per partition. Our experimental results on traffic density prediction using Long Short-Term Memory (LSTM) Neural Networks show that the partitioning-based models take 2x, if run sequentially, and 12x, if run in parallel, less training time, and 20x less prediction time compared to the unpartitioned model of the entire road infrastructure. The partitioning-based models take 100x less total sequential training time compared to single sensor models, i.e., one model per sensor. Furthermore, the partitioning-based models have 2x less prediction error (RMSE) compared to both the single sensor models and the entire road model. 

  • 19. Abbasi, A. G.
    et al.
    Muftic, Sead
    KTH, School of Information and Communication Technology (ICT), Communication: Services and Infrastucture, Communication Systems, CoS.
    Schmölzer, Gernot
    KTH, School of Information and Communication Technology (ICT), Communication: Services and Infrastucture, Communication Systems, CoS.
    A model and design of a security provider for Java applications2009In: International Conference for Internet Technology and Secured Transactions, ICITST 2009, 2009, p. 5402592-Conference paper (Refereed)
    Abstract [en]

    The model and design of a generic security provider provides a comprehensive set of security services, mechanisms, encapsulation methods, and security protocols for Java applications. The model is structured in four layers; each layer provides services to the upper layer and the top layer provide services to applications. The services reflect security requirements derived from a wide range of applications; from small desktop applications to large distributed enterprise environments. Based on the abstract model, this paper describes design and implementation of an instance of the provider comprising various generic security modules: symmetric key cryptography, asymmetric key cryptography, hashing, encapsulation, certificates management, creation and verification of signatures, and various network security protocols. This paper also describes the properties extensibility, flexibility, abstraction, and compatibility of the Java Security Provider.

  • 20. Abbasi, A. G.
    et al.
    Muftic, Sead
    KTH, School of Information and Communication Technology (ICT), Communication: Services and Infrastucture, Communication Systems, CoS.
    Schmölzer, Gernot
    KTH, School of Information and Communication Technology (ICT), Communication: Services and Infrastucture, Communication Systems, CoS.
    CryptoNET: A model of generic security provider2010In: International Journal of Internet Technology and Secured Transactions, ISSN 1748-569X, E-ISSN 1748-5703, Vol. 2, no 3-4, p. 321-335Article in journal (Refereed)
    Abstract [en]

    The model and design of a generic security provider provides a comprehensive set of security services, mechanisms, encapsulation methods, and security protocols for Java applications. The model is structured in four layers; each layer provides services to the upper layer and the top layer provide services to applications. The services reflect security requirements derived from a wide range of applications; from small desktop applications to large distributed enterprise environments. Based on the abstract model, this paper describes design and implementation of an instance of the provider comprising various generic security modules: symmetric key cryptography, asymmetric key cryptography, hashing, encapsulation, certificates management, creation and verification of signatures, and various network security protocols. This paper also describes the properties for extensibility, flexibility, abstraction, and compatibility of the Java security provider.

  • 21.
    Abbasi, Abdul Ghafoor
    et al.
    KTH, School of Information and Communication Technology (ICT), Communication: Services and Infrastucture, Communication Systems, CoS.
    Muftic, Sead
    KTH, School of Information and Communication Technology (ICT), Communication: Services and Infrastucture, Communication Systems, CoS.
    Mumtaz, Shahzad Ahmed
    KTH, School of Information and Communication Technology (ICT), Communication: Services and Infrastucture, Communication Systems, CoS.
    Security extensions of windows environment based on FIPS 201 (PIV) smart card2011In: World Congr. Internet Secur., WorldCIS, 2011, p. 86-92Conference paper (Refereed)
    Abstract [en]

    This paper describes security extensions of various Windows components based on usage of FIPS 201 (PIV) smart cards. Compared to some other similar solutions, this system has two significant advantages: first, smart cards are based on FIPS 201 standard and not on some proprietary technology; second, smart card security extensions represent an integrated solution, so the same card is used for security of several Microsoft products. Furthermore, our smart card system uses FIPS 201 applet and middleware with smart card APIs, so it can also be used by other developers to extend their own applications with smart card functions in a Windows environment. We support the following security features with smart cards: start-up authentication (based on PIN and/or fingerprint), certificate-based domain authentication, strong authentication, and protection of local resources. We also integrated our middleware and smart cards with MS Outlook and MS Internet Explorer.

  • 22.
    ABBASI, MUHAMMAD MOHSIN
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Solving Sudoku by Sparse Signal Processing2015Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Sudoku is a discrete constraints satisfaction problem which is modeled as an underdetermined linear

    system. This report focuses on applying some new signal processing approaches to solve sudoku and

    comparisons to some of the existing approaches are implemented. As our goal is not meant for

    sudoku only in the long term, we applied approximate solvers using optimization theory methods. A

    Semi Definite Relaxation (SDR) convex optimization approach was developed for solving sudoku. The

    idea of Iterative Adaptive Algorithm for Amplitude and Phase Estimation (IAA-APES) from array

    processing is also being used for sudoku to utilize the sparsity of the sudoku solution as is the case in

    sensing applications. LIKES and SPICE were also tested on sudoku and their results are compared with

    l1-norm minimization, weighted l1-norm, and sinkhorn balancing. SPICE and l1-norm are equivalent

    in terms of accuracy, while SPICE is slower than l1-norm. LIKES and weighted l1-norm are equivalent

    and better than SPICE and l1-norm in accuracy. SDR proved to be best when the sudoku solutions are

    unique; however the computational complexity is worst for SDR. The accuracy for IAA-APES is

    somewhere between SPICE and LIKES and its computation speed is faster than both.

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  • 23. Abbeloos, W.
    et al.
    Ataer-Cansizoglu, E.
    Caccamo, Sergio
    KTH.
    Taguchi, Y.
    Domae, Y.
    3D object discovery and modeling using single RGB-D images containing multiple object instances2018In: Proceedings - 2017 International Conference on 3D Vision, 3DV 2017, Institute of Electrical and Electronics Engineers (IEEE), 2018, p. 431-439Conference paper (Refereed)
    Abstract [en]

    Unsupervised object modeling is important in robotics, especially for handling a large set of objects. We present a method for unsupervised 3D object discovery, reconstruction, and localization that exploits multiple instances of an identical object contained in a single RGB-D image. The proposed method does not rely on segmentation, scene knowledge, or user input, and thus is easily scalable. Our method aims to find recurrent patterns in a single RGB-D image by utilizing appearance and geometry of the salient regions. We extract keypoints and match them in pairs based on their descriptors. We then generate triplets of the keypoints matching with each other using several geometric criteria to minimize false matches. The relative poses of the matched triplets are computed and clustered to discover sets of triplet pairs with similar relative poses. Triplets belonging to the same set are likely to belong to the same object and are used to construct an initial object model. Detection of remaining instances with the initial object model using RANSAC allows to further expand and refine the model. The automatically generated object models are both compact and descriptive. We show quantitative and qualitative results on RGB-D images with various objects including some from the Amazon Picking Challenge. We also demonstrate the use of our method in an object picking scenario with a robotic arm.

  • 24. Abd El Ghany, M. A.
    et al.
    El-Moursy, M. A.
    Ismail, Mohammed
    KTH, School of Information and Communication Technology (ICT), Electronic Systems.
    High throughput architecture for CLICHÉ network on chip2009In: Proceedings - IEEE International SOC Conference, SOCC 2009, 2009, p. 155-158Conference paper (Refereed)
    Abstract [en]

    High Throughput Chip-Level Integration of Communicating Heterogeneous Elements (CLICHÉ) architecture to achieve high performance Networks on Chip (NoC) is proposed. The architecture increases the throughput of the network by 40% while preserving the average latency. The area of High Throughput CLICHÉ switch is decreased by 18% as compared to CLICHÉ switch. The total metal resources required to implement High Throughput CLICHÉ design is increased by 7% as compared to the total metal resources required to implement CLICHÉ design. The extra power consumption required to achieve the proposed architecture is 8% of the total power consumption of the CLICHÉ architecture.

  • 25. Abd El Ghany, M. A.
    et al.
    El-Moursy, M. A.
    Ismail, Mohammed
    KTH, School of Information and Communication Technology (ICT), Electronic Systems. Ohio State University, Columbus, United States .
    High throughput architecture for high performance NoC2009In: ISCAS: 2009 IEEE International Symposium on Circuits and Systems, IEEE , 2009, p. 2241-2244Conference paper (Refereed)
    Abstract [en]

    High Throughput Butterfly Fat Tree (HTBFT) architecture to achieve high performance Networks on Chip (NoC) is proposed. The architecture increases the throughput of the network by 38% while preserving the average latency. The area of HTBFT switch is decreased by 18% as compared to Butterfly Fat Tree switch. The total metal resources required to implement HTBFT design is increased by 5% as compared to the total metal resources required to implement BFT design. The extra power consumption required to achieve the proposed architecture is 3% of the total power consumption of the BFT architecture.

  • 26. Abd El Ghany, M. A.
    et al.
    El-Moursy, M. A.
    Korzec, D.
    Ismail, Mohammed
    KTH, School of Information and Communication Technology (ICT), Integrated Devices and Circuits. Ohio State University, Columbus, OH, United States .
    Asynchronous BFT for low power networks on chip2010In: ISCAS 2010 - 2010 IEEE International Symposium on Circuits and Systems: Nano-Bio Circuit Fabrics and Systems, IEEE , 2010, p. 3240-3243Conference paper (Refereed)
    Abstract [en]

    Asynchronous Butterfly Fat Tree (BFT) architecture is proposed to achieve low power Network on Chip (NoC). Asynchronous design could reduce the power dissipation of the network if the activity factor of the data transfer between two switches (αdata satisfies a certain condition. The area of Asynchronous BFT switch is increased by 25% as compared to Synchronous switch. However, the power dissipation of the Asynchronous architecture could be decreased by up to 33% as compared to the power dissipation of the conventional Synchronous architecture when the αdata equals 0.2 and the activity factor of the control signals is equal to 1/64 of the αdata. The total metal resources required to implement Asynchronous design is decreased by 12%.

  • 27. Abd El Ghany, M. A.
    et al.
    El-Moursy, M. A.
    Korzec, D.
    Ismail, Mohammed
    KTH, School of Information and Communication Technology (ICT), Integrated Devices and Circuits. Ohio State University, Columbus, OH, United States .
    Power characteristics of networks on chip2010In: ISCAS 2010 - 2010 IEEE International Symposium on Circuits and Systems: Nano-Bio Circuit Fabrics and Systems, IEEE , 2010, p. 3721-3724Conference paper (Refereed)
    Abstract [en]

    Power characteristics of different Network on Chip (NoC) topologies are developed. Among different NoC topologies, the Butterfly Fat Tree (BFT) dissipates the minimum power. With the advance in technology, the relative power consumption of the interconnects and the associate repeaters of the BFT decreases as compared to the power consumption of the network switches. The power dissipation of interswitch links and repeaters for BFT represents only 1% of the total power dissipation of the network. In addition of providing high throughput, the BFT is a power efficient topology for NoCs.

  • 28. Abd El Ghany, M. A.
    et al.
    El-Moursy, M. A.
    Korzec, D.
    Ismail, Mohammed
    KTH, School of Information and Communication Technology (ICT), Integrated Devices and Circuits.
    Power efficient networks on chip2009In: 2009 16th IEEE International Conference on Electronics, Circuits and Systems, ICECS 2009, 2009, p. 105-108Conference paper (Refereed)
    Abstract [en]

    a low power switch design is proposed to achieve power-efficient Network on Chip (NoC). The proposed NoC switch reduce. The power consumption oy the Butterfly Fat Tree (BFT) architecture by 28 % as compared to the conventional BFT switch. Moreover. The power reduction technique is applied to different NoC architectures. The technique reduce. The power consumption oy the network by up to 41%. Whe. The power consumption oy the whole network includin. The interswich links and repeaters is taken into account. The overall power consumption is decreased by up to 33% at the maximum operating frequency oy the switch. The BFT architecture consume. The minimum power as compared to other NoC architectures.

  • 29. Abd Elghany, M. A.
    et al.
    El-Moursy, M. A.
    Korzec, D.
    Ismail, Mohammed
    KTH, School of Information and Communication Technology (ICT), Integrated Devices and Circuits. Ohio State University, United States .
    High throughput architecture for OCTAGON network on chip2009In: 2009 16th IEEE International Conference on Electronics, Circuits and Systems, ICECS 2009, IEEE , 2009, p. 101-104Conference paper (Refereed)
    Abstract [en]

    High Throughput Octagon architecture to achieve high performance Networks on Chip (NoC) is proposed. The architecture increase. The throughput oy the network by 17% while preservin. The average latency. The area of High Throughput OCTAGON switch is decreased by 18% as compared to OCTAGON switch. The total metal resources required to implement High Throughput OCTAGON design is increased by 8% as compared to the total metal resources required to implement OCTAGON design. The extra power consumption required to achiev. The proposed architecture is 2% oy the total power consumption oy the OCTAGON architecture.

  • 30.
    Abdalla, Osman
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Health Informatics and Logistics.
    Design and implementation of a signaling system for a novel light-baseed bioprinter: Design och implementering av ett signalsystem för en ny ljusbaserad bioprinter2023Independent thesis Basic level (university diploma), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    A 3D bioprinter employing light-based technology has been designed and constructed in an EU-funded research initiative known as BRIGHTER (Bioprinting by Light-Sheet Lithography). This initiative is a collaborative effort between institutions and companies and aims to develop a technique for efficient and accurate production of engineered tissue.

    Presently, the bioprinter’s function is limited to 2D printing, with the lack of 3D printing capabilities. 

    The problem addressed is the integration of two separate electronic systems within the bioprinter to control the laser beam’s trajectory for 3D printing. The goal of the project is to create functional software and simulation tools to control the hardware modules in a precise and synchronized manner, thereby enabling 3D printing.

    The outcome manifests as a software prototype, which successfully facilitates intercommunication between the two electronic subsystems within the bioprinter, thereby enabling further progress on the bioprinter with 3D printing available. Nevertheless, the prototype requires thorough testing to determine its optimal operational efficiency in terms of timing the movements for the various hardware modules.

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    Bioprinter
  • 31.
    Abdalmoaty, Mohamed
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Learning Stochastic Nonlinear Dynamical Systems Using Non-stationary Linear Predictors2017Licentiate thesis, monograph (Other academic)
    Abstract [en]

    The estimation problem of stochastic nonlinear parametric models is recognized to be very challenging due to the intractability of the likelihood function. Recently, several methods have been developed to approximate the maximum likelihood estimator and the optimal mean-square error predictor using Monte Carlo methods. Albeit asymptotically optimal, these methods come with several computational challenges and fundamental limitations.

    The contributions of this thesis can be divided into two main parts. In the first part, approximate solutions to the maximum likelihood problem are explored. Both analytical and numerical approaches, based on the expectation-maximization algorithm and the quasi-Newton algorithm, are considered. While analytic approximations are difficult to analyze, asymptotic guarantees can be established for methods based on Monte Carlo approximations. Yet, Monte Carlo methods come with their own computational difficulties; sampling in high-dimensional spaces requires an efficient proposal distribution to reduce the number of required samples to a reasonable value.

    In the second part, relatively simple prediction error method estimators are proposed. They are based on non-stationary one-step ahead predictors which are linear in the observed outputs, but are nonlinear in the (assumed known) input. These predictors rely only on the first two moments of the model and the computation of the likelihood function is not required. Consequently, the resulting estimators are defined via analytically tractable objective functions in several relevant cases. It is shown that, under mild assumptions, the estimators are consistent and asymptotically normal. In cases where the first two moments are analytically intractable due to the complexity of the model, it is possible to resort to vanilla Monte Carlo approximations. Several numerical examples demonstrate a good performance of the suggested estimators in several cases that are usually considered challenging.

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    fulltext
  • 32.
    Abdalmoaty, Mohamed R.
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Hjalmarsson, Håkan
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (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.

  • 33.
    Abdalmoaty, Mohamed R.
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Rojas, Cristian R.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Hjalmarsson, Håkan
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (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.

  • 34.
    Abdalmoaty, Mohamed
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Eriksson, Oscar
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Software and Computer systems, SCS.
    Bereza-Jarocinski, Robert
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Broman, David
    KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Software and Computer systems, SCS.
    Hjalmarsson, Håkan
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Identification of Non-Linear Differential-Algebraic Equation Models with Process Disturbances2021In: Proceedings The 60th IEEE conference on Decision and Control (CDC), Institute of Electrical and Electronics Engineers (IEEE) , 2021Conference paper (Refereed)
    Abstract [en]

    Differential-algebraic equations (DAEs) arise naturally as a result of equation-based object-oriented modeling. In many cases, these models contain unknown parameters that have to be estimated using experimental data. However, often the system is subject to unknown disturbances which, if not taken into account in the estimation, can severely affect the model's accuracy. For non-linear state-space models, particle filter methods have been developed to tackle this issue. Unfortunately, applying such methods to non-linear DAEs requires a transformation into a state-space form, which is particularly difficult to obtain for models with process disturbances. In this paper, we propose a simulation-based prediction error method that can be used for non-linear DAEs where disturbances are modeled as continuous-time stochastic processes. To the authors' best knowledge, there are no general methods successfully dealing with parameter estimation for this type of model. One of the challenges in particle filtering  methods are random variations in the minimized cost function due to the nature of the algorithm. In our approach, a similar phenomenon occurs and we explicitly consider how to sample the underlying continuous process to mitigate this problem. The method is illustrated numerically on a pendulum example. The results suggest that the method is able to deliver consistent estimates.

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    fulltext
  • 35.
    Abdalmoaty, Mohamed
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Henrion, D.
    Rodrigues, L.
    Measures and LMIs for optimal control of piecewise-affine systems2013In: 2013 European Control Conference, ECC 2013, IEEE, 2013, p. 3173-3178, article id 6669627Conference paper (Refereed)
    Abstract [en]

    This paper considers the class of deterministic continuous-time optimal control problems (OCPs) with piecewise-affine (PWA) vector field, polynomial Lagrangian and semialgebraic input and state constraints. The OCP is first relaxed as an infinite-dimensional linear program (LP) over a space of occupation measures. This LP is then approached by an asymptotically converging hierarchy of linear matrix inequality (LMI) relaxations. The relaxed dual of the original LP returns a polynomial approximation of the value function that solves the Hamilton-Jacobi-Bellman (HJB) equation of the OCP. Based on this polynomial approximation, a suboptimal policy is developed to construct a state feedback in a sample-and-hold manner. The results show that the suboptimal policy succeeds in providing a suboptimal state feedback law that drives the system relatively close to the optimal trajectories and respects the given constraints.

  • 36.
    Abdalmoaty, Mohamed
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Hjalmarsson, Håkan
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    A Simulated Maximum Likelihood Method for Estimation of Stochastic Wiener Systems2016In: 2016 IEEE 55th Conference on Decision and Control, CDC 2016, Institute of Electrical and Electronics Engineers (IEEE), 2016, p. 3060-3065, article id 7798727Conference paper (Refereed)
    Abstract [en]

    This paper introduces a simulation-based method for maximum likelihood estimation of stochastic Wienersystems. It is well known that the likelihood function ofthe observed outputs for the general class of stochasticWiener systems is analytically intractable. However, when the distributions of the process disturbance and the measurement noise are available, the likelihood can be approximated byrunning a Monte-Carlo simulation on the model. We suggest the use of Laplace importance sampling techniques for the likelihood approximation. The algorithm is tested on a simple first order linear example which is excited only by the process disturbance. Further, we demonstrate the algorithm on an FIR system with cubic nonlinearity. The performance of the algorithm is compared to the maximum likelihood method and other recent techniques.

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    fulltext
  • 37.
    Abdalmoaty, Mohamed
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Hjalmarsson, Håkan
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Application of a Linear PEM Estimator to a Stochastic Wiener-Hammerstein Benchmark Problem2018In: 18th IFAC Symposium on System Identification, 2018Conference paper (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 presentedand discussed.

    Download full text (pdf)
    0028.pdf
  • 38.
    Abdalmoaty, Mohamed
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Hjalmarsson, Håkan
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Consistent Estimators of Stochastic MIMO Wiener Models based on Suboptimal Predictors2018Conference paper (Refereed)
    Download full text (pdf)
    fulltext
  • 39.
    Abdalmoaty, Mohamed
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Hjalmarsson, Håkan
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Identification of Stochastic Nonlinear Models Using Optimal Estimating Functions2020In: Automatica, ISSN 0005-1098, E-ISSN 1873-2836, Vol. 119, article id 109055Article in journal (Refereed)
    Abstract [en]

    The first part of the paper examines the asymptotic properties of linear prediction error method estimators, which were recently suggested for the identification of nonlinear stochastic dynamical models. It is shown that their accuracy depends not only on the shape of the unknown distribution of the data, but also on how the model is parameterized. Therefore, it is not obvious in general which linear prediction error method should be preferred. In the second part, the estimating functions approach is introduced and used to construct estimators that are asymptotically optimal with respect to a specific class of estimators. These estimators rely on a partial probabilistic parametric models, and therefore neither require the computations of the likelihood function nor any marginalization integrals. The convergence and consistency of the proposed estimators are established under standard regularity and identifiability assumptions akin to those of prediction error methods. The paper is concluded by several numerical simulation examples.

    Download full text (pdf)
    fulltext
  • 40.
    Abdalmoaty, Mohamed
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Hjalmarsson, Håkan
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (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.

    Download full text (pdf)
    fulltext
    Download full text (pdf)
    fulltext
  • 41.
    Abdalmoaty, Mohamed
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Hjalmarsson, Håkan
    KTH, School of Electrical Engineering (EES), Automatic Control.
    On Re-Weighting, Regularization Selection, and Transient in Nuclear Norm Based Identification2015Conference paper (Refereed)
    Abstract [en]

    In this contribution, we consider the classical problem of estimating an Output Error model given a set of input-output measurements. First, we develop a regularization method based on the re-weighted nuclear norm heuristic. We show that the re-weighting improves the estimate in terms of better fit. Second, we suggest an implementation method that helps in eliminating the regularization parameters from the problem by introducing a constant based on a validation criterion. Finally, we develop a method for considering the effect of the transient when the initial conditions are unknown. A simple numerical example is used to demonstrate the proposed method in comparison to classical and another recent method based on the nuclear norm heuristic.

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    fulltext
  • 42.
    Abdalmoaty, Mohamed
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Hjalmarsson, Håkan
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Simulated Pseudo Maximum Likelihood Identification of Nonlinear Models2017In: The 20th IFAC World Congress, Elsevier, 2017, Vol. 50, p. 14058-14063Conference paper (Refereed)
    Abstract [en]

    Nonlinear stochastic parametric models are widely used in various fields. However, for these models, the problem of maximum likelihood identification is very challenging due to the intractability of the likelihood function. Recently, several methods have been developed to approximate the analytically intractable likelihood function and compute either the maximum likelihood or a Bayesian estimator. These methods, albeit asymptotically optimal, are computationally expensive. In this contribution, we present a simulation-based pseudo likelihood estimator for nonlinear stochastic models. It relies only on the first two moments of the model, which are easy to approximate using Monte-Carlo simulations on the model. The resulting estimator is consistent and asymptotically normal. We show that the pseudo maximum likelihood estimator, based on a multivariate normal family, solves a prediction error minimization problem using a parameterized norm and an implicit linear predictor. In the light of this interpretation, we compare with the predictor defined by an ensemble Kalman filter. Although not identical, simulations indicate a close relationship. The performance of the simulated pseudo maximum likelihood method is illustrated in three examples. They include a challenging state-space model of dimension 100 with one output and 2 unknown parameters, as well as an application-motivated model with 5 states, 2 outputs and 5 unknown parameters.

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  • 43.
    Abdalmoaty, Mohamed
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Hjalmarsson, Håkan
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    Wahlberg, Bo
    KTH, School of Electrical Engineering and Computer Science (EECS), Intelligent systems, Decision and Control Systems (Automatic Control).
    The Gaussian MLE versus the Optimally weighted LSE2020In: IEEE signal processing magazine (Print), ISSN 1053-5888, E-ISSN 1558-0792, Vol. 37, no 6, p. 195-199Article in journal (Refereed)
    Abstract [en]

    In this note, we derive and compare the asymptotic covariance matrices of two parametric estimators: the Gaussian Maximum Likelihood Estimator (MLE), and the optimally weighted Least-Squares Estimator (LSE). We assume a general model parameterization where the model's mean and variance are jointly parameterized, and consider Gaussian and non-Gaussian data distributions.

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    fulltext
  • 44.
    Abdalmoaty, Mohamed
    et al.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Rojas, Cristian R.
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Hjalmarsson, Håkan
    KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Identication of a Class of Nonlinear Dynamical Networks2018Conference paper (Refereed)
    Abstract [en]

    Identifcation 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.

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    0131.pdf
  • 45.
    Abdel Hussein, Mustafa
    KTH, School of Electrical Engineering (EES).
    Modeling and Control of Unmanned Air Vehicles2015Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
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  • 46. Abdelhakim, A.
    et al.
    Blaabjerg, F.
    Nee, Hans-Peter
    KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electric Power and Energy Systems.
    Single-Stage Boost Modular Multilevel Converter (BMMC) for Energy Storage Interface2020In: 2020 22nd European Conference on Power Electronics and Applications, EPE 2020 ECCE Europe, Institute of Electrical and Electronics Engineers (IEEE) , 2020, article id 9215788Conference paper (Refereed)
    Abstract [en]

    Single-stage DC-AC power converters are gaining higher attention due to their simpler structure compared to the two-stage equivalent solution. In this paper, a single-stage DC-AC converter solution is proposed for interfacing a low voltage (LV) DC source with a higher voltage AC load or grid, where this converter has a modular structure with multilevel operation. The proposed converter, which is called boost modular multilevel converter (BMMC), comprises the boosting capability within the inversion operation, and it is mainly dedicated for interfacing LV energy storage systems, such as fuel cells and batteries, and it allows the use of LV MOSFETs (« 300 V), in order to utilize their low ON-state resistance, along with LV electrolytic capacitors. This converter is introduced and analysed in this paper, where simulation results using PLECS, considering a 10 kW three-phase BMMC, are presented in order to verify its functionality.

  • 47.
    AbdElKhalek, Y. M.
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS).
    Awad, M. I.
    Abd El Munim, H. E.
    Maged, S. A.
    Trajectory-based fast ball detection and tracking for an autonomous industrial robot system2021In: International Journal of Intelligent Systems Technologies and Applications, ISSN 1740-8865, E-ISSN 1740-8873, Vol. 20, no 2, p. 126-145Article in journal (Refereed)
    Abstract [en]

    Autonomising industrial robots is the main goal in this paper; imagine humanoid robots that have several degrees of freedom (DOF) mechanisms as their arms. What if the humanoid's arms could be programmed to be responsive to their surrounding environment, without any hard-coding assigned? This paper presents the idea of an autonomous system, where the system observes the surrounding environment and takes action on its observation. The application here is that of rebuffing an object that is thrown towards a robotic arm's workspace. This application mimics the idea of high dynamic responsiveness of a robot's arm. This paper will present a trajectory generation framework for rebuffing incoming flying objects. The framework bases its assumptions on inputs acquired through image processing and object detection. After extensive testing, it can be said that the proposed framework managed to fulfil the real-time system requirements for this application, with an 80% successful rebuffing rate. 

  • 48.
    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.

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    Designing electricity distribution network charges for an efficient integration of distributed energy resources and customer response
  • 49.
    Abdi Kelishami, Alireza
    KTH, School of Electrical Engineering (EES), Communication Networks.
    Secure Privacy-Friendly Instant Messaging (IM) for Guidepal2015Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    It is fascinating, and yet often neglected, that a user’s privacy can be invaded notonly by the absence of security measures and mechanisms, but also by improperor inadequate usage of security services and mechanisms. When designingsecure systems, we must consider what services are needed and what is not.The work in this thesis revolves around privacy-friendly instant messaging (IM)systems. In such a system, an inadequate usage of security measures leads tohaving IM servers being able to intercept or gather users’ private conversations.An improper usage of security measures could bring about non-repudiationwhich is desirable when signing contracts, but unwelcome in IM and privateconversations.We will look into requirements of the desired IM system, study the currentstate-of-the-art solutions, deploy an IM server, and briefly extend an existingmodern privacy-friendly IM protocol and an open source mobile application tomeet our security and privacy requirements. This extended IM application iscalled Guidepal-IM and is available as open source1The thesis work is introduced and carried out at Guidepal, a startup companyin Stockholm. It is therefore supervised partly at Guidepal and partly at KTH.Since Guidepal is also looking into possibilities of integrating an IM featureto its current social media apps, our contribution would also briefly extend tostudying the limitations and recommendations for Guidepal’s social media appto help user privacy preservation.

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    fulltext
  • 50.
    Abdirahman Adami, Adnan
    KTH, School of Electrical Engineering and Computer Science (EECS).
    Actors Cooperation Analysis: A Techo-economic Study on Smart City Paradigm2019Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Modern cities must overcome complex challenges to achieve socio-economic development and to improve the quality of life as the urban population is rapidly increasing. The concept of smart citie s is a response to these challenges. Thus, emerging technologies that are key enablers for the development of a smart city are said to be IoT and 5G. To deploy such technologies , however, may be expensive and requires the involvement of multiple actors. Hence, lack of cooperation and coordination for planning, financing, deploying and managing the city’s operational networks makes it even more difficult to overcome such challenges. Further, waste management companies and parking services operators in a city have expensive operation costs and services inefficiency due to little utilization of IoT-based solutions. This paper identifies and analyzes smart city ecosyst e ms, value networks, actors, actor’s roles, and business models in order to illustrate business relationships and provide business opportunities in the development of smart and sustainable cities through cooperation and collaboration among involved actors . Target actors that this study focuse s are on Mobile Network Operators, Parking Services Operators, and Waste Management Companies, and uses smart parking and smart waste collection as use-cases. Results show several cooperative business scenarios that can lead to successful business relationships and opportunities.

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