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  • 11901. Zhi, Ruicong
    et al.
    Flierl, Markus
    KTH, Skolan för elektro- och systemteknik (EES), Ljud- och bildbehandling (Stängd 130101).
    Ruan, Qiuqi
    Kleijn, W. Bastiaan
    KTH, Skolan för elektro- och systemteknik (EES), Centra, ACCESS Linnaeus Centre. KTH, Skolan för elektro- och systemteknik (EES), Ljud- och bildbehandling (Stängd 130101).
    Facial expression recognition based on graph-preserving sparse non-negative matrix factorization2009Konferansepaper (Fagfellevurdert)
    Abstract [en]

    In this paper, we present a novel algorithm for representing facial expressions. The algorithm is based on the non-negative matrix factorization (NMF) algorithm, which decomposes the original facial image matrix into two non-negative matrices, namely the coefficient matrix and the basis image matrix. We call the novel algorithm graph-preserving sparse non-negative matrix factorization (GSNMF). GSNMF utilizes both sparse and graph-preserving constraints to achieve a non-negative factorization. The graph-preserving criterion preserves the structure of the original facial images in the embedded sub-space while considering the class information of the facial images. Therefore, GSNMF has more discriminant power than NMF. GSNMF is applied to facial images for the recognition of six basic facial expressions. Our experiments show that GSNMF achieves on average a recognition rate of 93.5% compared to that of discriminant NMF with 91.6%.

  • 11902. Zhong, Jianghua
    et al.
    Cheng, Daizhan
    Hu, Xiaoming
    KTH, Skolan för teknikvetenskap (SCI), Matematik (Inst.), Optimeringslära och systemteori. KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS. KTH, Skolan för elektro- och systemteknik (EES), Centra, ACCESS Linnaeus Centre.
    Constructive stabilization for quadratic input nonlinear systems2008Inngår i: Automatica, ISSN 0005-1098, E-ISSN 1873-2836, Vol. 44, nr 8, s. 1996-2005Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    In this paper stabilization of nonlinear systems with quadratic multi-input is considered. With the help of control Lyapunov function (CLF), a constructive parameterization of controls that globally asymptotically stabilize the system is proposed. Two different cases are considered. Firstly, under certain regularity assumptions. the feasible control set is parameterized, and Continuous feedback stabilizing controls are designed. Then for the general case. piecewise Continuous stabilizing controls are proposed. The design procedure can also be used to verify whether a candidate CLF is indeed a CLF. Several illustrative examples are presented as well.

  • 11903.
    Zhong, Jianghua
    et al.
    KTH, Skolan för teknikvetenskap (SCI), Matematik (Inst.), Optimeringslära och systemteori. KTH, Skolan för elektro- och systemteknik (EES), Centra, ACCESS Linnaeus Centre.
    Hu, Xiaoming
    KTH, Skolan för teknikvetenskap (SCI), Matematik (Inst.), Optimeringslära och systemteori. KTH, Skolan för elektro- och systemteknik (EES), Centra, ACCESS Linnaeus Centre.
    Kleijn, W. Bastiaan
    KTH, Skolan för elektro- och systemteknik (EES), Ljud- och bildbehandling. KTH, Skolan för elektro- och systemteknik (EES), Centra, ACCESS Linnaeus Centre.
    Kozica, Ermin
    KTH, Skolan för elektro- och systemteknik (EES), Ljud- och bildbehandling. KTH, Skolan för elektro- och systemteknik (EES), Centra, ACCESS Linnaeus Centre.
    Constructive camera pose control for optimizing multiview distributed video coding2008Inngår i: Proceedings of the IEEE Conference on Decision and Control, 2008, s. 3372-3379Konferansepaper (Fagfellevurdert)
    Abstract [en]

    In this paper camera pose control for optimizing multiview distributed video coding is considered. The scenario considered is that multiple agents with monocular cameras observe a common scene in a three dimensional world. To get a good video reconstruction under a transmission rate constraint, the camera closest to the center of the camera array is chosen as the reference camera. The poses of all other cameras are controlled and designed such that their images are maximally similar under a constraint on their separation. Based on the rigid motion allowed for the cameras, two cases are considered. For the case where the rigid motion only involves translation, translation control is designed. For the case where it involves both translation and rotation, both controls are constructed. Some simulated results are given to show the efficiency of the designed controllers.

  • 11904.
    Zhong, Tingye
    KTH, Skolan för elektroteknik och datavetenskap (EECS).
    Exploring interaction design for mindful breathing support: the HU II design case2018Independent thesis Advanced level (degree of Master (Two Years)), 20 poäng / 30 hpOppgave
    Abstract [en]

    Mindfulness-based stress reduction (MBSR) is an effective method of stress treatment and prevention. One of the interactive systems aiming at supporting MBSR is HU. As a continuous work of HU, a device aiding mindful breathing called HU II was developed and evaluated. The paper investigates the real-time interaction between the user and the HU II including the performance of the deployed sensor as well as the representation and mapping of chosen modalities. Ten participants with different backgrounds and knowledge levels of mindfulness evaluated the device and gave their subjective opinions and feedback. The results indicate that the employed sensor and modalities support real-time interaction for mindful breathing. Via these results, further research possibilities and guidelines, which can help the design of future mindfulness-based solutions were suggested.

  • 11905.
    Zhong, Yang
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Medieteknik och interaktionsdesign, MID.
    Hedman, Anders
    KTH, Skolan för datavetenskap och kommunikation (CSC), Medieteknik och interaktionsdesign, MID.
    Li, Haibo
    KTH, Skolan för datavetenskap och kommunikation (CSC), Medieteknik och interaktionsdesign, MID.
    How Good Can a Face Identifier Be Without Learning2016Inngår i: Lecture Notes in Computer Science, ISSN 0302-9743, E-ISSN 1611-3349Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Constructing discriminative features is an essential issue in developing face recognition algorithms. There are two schools in how features are constructed: hand-crafted features and learned features from data. A clear trend in the face recognition community is to use learned features to replace hand-crafted ones for face recognition, due to the superb performance achieved by learned features through Deep Learning networks. Given the negative aspects of database-dependent solutions, we consider an alternative and demonstrate that, for good generalization performance, developing face recognition algorithms by using handcrafted features is surprisingly promising when the training dataset is small or medium sized. We show how to build such a face identifier with our Block Matching method which leverages the power of the Gabor phase in face images. Although no learning process is involved, empirical results show that the performance of this “designed” identifier is comparable (superior) to state-of-the-art identifiers and even close to Deep Learning approaches.

  • 11906.
    Zhong, Yang
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Medieteknik och interaktionsdesign, MID.
    Hedman, Anders
    KTH, Skolan för datavetenskap och kommunikation (CSC), Medieteknik och interaktionsdesign, MID.
    Li, Haibo
    KTH, Skolan för datavetenskap och kommunikation (CSC), Medieteknik och interaktionsdesign, MID.
    How good can a face identifier be without learning?2017Inngår i: 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, VISIGRAPP 2016, Springer, 2017, Vol. 693, s. 515-533Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Constructing discriminative features is an essential issue in developing face recognition algorithms. There are two schools in how features are constructed: hand-crafted features and learned features from data. A clear trend in the face recognition community is to use learned features to replace hand-crafted ones for face recognition, due to the superb performance achieved by learned features through Deep Learning networks. Given the negative aspects of database-dependent solutions, we consider an alternative and demonstrate that, for good generalization performance, developing face recognition algorithms by using hand-crafted features is surprisingly promising when the training dataset is small or medium sized. We show how to build such a face identifier with our Block Matching method which leverages the power of the Gabor phase in face images. Although no learning process is involved, empirical results show that the performance of this “designed” identifier is comparable (superior) to state-of-the-art identifiers and even close to Deep Learning approaches.

  • 11907. Zhong, Yang
    et al.
    Li, Haibo
    KTH, Skolan för datavetenskap och kommunikation (CSC), Medieteknik och interaktionsdesign, MID.
    Is block matching an alternative tool to LBP for face recognition?2014Konferansepaper (Fagfellevurdert)
    Abstract [en]

    In this paper, we introduce the Block Matching (BM) as an alternative patch-based local matching approach for solving the face recognition problem. The Block Matching enables an image patch of the probe face image to search for its best matching from displaced positions in the gallery face image. This matching strategy is very effective for handling spatial shift between two images and it is radically different from that of the widely used LBP type patch-based local matching approaches. Our evaluations on the FERET and CMU-PIE databases show that the performance of this simple method is well comparable (superior) to that of the popular LBP approach. We argue that the Block Matching could provide face recognition a new approach with more flexible algorithm architecture. One can expect that it could lead to much higher performance when combining with other feature extraction techniques, like Gabor wavelet and deep learning.

  • 11908.
    Zhong, Yang
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Medieteknik och interaktionsdesign, MID.
    Li, Haibo
    KTH, Skolan för datavetenskap och kommunikation (CSC), Medieteknik och interaktionsdesign, MID.
    Leveraging Gabor Phase for Face Identification in Controlled Scenarios2016Inngår i: Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, Science and Technology Publications,Lda , 2016, s. 49-58Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Gabor features have been widely employed in solving face recognition problems in controlled scenarios. To construct discriminative face features from the complex Gabor space, the amplitude information is commonly preferred, while the other one — the phase — is not well utilized due to its spatial shift sensitivity. In this paper, we address the problem of face recognition in controlled scenarios. Our focus is on the selection of a suitable signal representation and the development of a better strategy for face feature construction. We demonstrate that through our Block Matching scheme Gabor phase information is powerful enough to improve the performance of face identification. Compared to state of the art Gabor filtering based approaches, the proposed algorithm features much lower algorithmic complexity. This is mainly due to our Block Matching enables the employment of high definition Gabor phase. Thus, a single-scale Gabor frequency band is sufficient for discrimination. Furthermore, learning process is not involved in the facial feature construction, which avoids the risk of building a database-dependent algorithm. Benchmark evaluations show that the proposed learning-free algorith outperforms state-of-the-art Gabor approaches and is even comparable to Deep Learning solutions.

  • 11909.
    Zhong, Yang
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Medieteknik och interaktionsdesign, MID.
    Sullivan, Josephine
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Li, Haibo
    KTH, Skolan för datavetenskap och kommunikation (CSC), Medieteknik och interaktionsdesign, MID.
    Face Attribute Prediction Using Off-The-Shelf CNN Features2016Inngår i: 2016 International Conference on Biometrics, ICB 2016, Institute of Electrical and Electronics Engineers (IEEE), 2016, artikkel-id 7550092Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Predicting attributes from face images in the wild is a challenging computer vision problem. To automatically describe face attributes from face containing images, traditionally one needs to cascade three technical blocks — face localization, facial descriptor construction, and attribute classification — in a pipeline. As a typical classification problem, face attribute preiction has been addressed using deep learning. Current state-of-the-art performance was achieved by using two cascaded Convolutional Neural Networks (CNNs), which were specifically trained to learn face localization and attribute description. In this paper, we experiment with an alternative way of employing the power of deep representations from CNNs. Combining with conventional face localization techniques, we use off-the-shelf architectures trained for face recognition to build facial descriptors. Recognizing that the describable face attributes are diverse, our face descriptors are constructed from different levels of the CNNs for different attributes to best facilitate face attribute prediction. Experiments on two large datasets, LFWA and CelebA, show that our approach is entirely comparable to the state-of-the-art. Our findings not only demonstrate an efficient face attribute prediction approach, but also raise an important question: how to leverage the power of off-the-shelf CNN representations for novel tasks

  • 11910.
    Zhong, Yang
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Medieteknik och interaktionsdesign, MID.
    Sullivan, Josephine
    KTH, Skolan för datavetenskap och kommunikation (CSC), Robotik, perception och lärande, RPL.
    Li, Haibo
    KTH, Skolan för datavetenskap och kommunikation (CSC), Medieteknik och interaktionsdesign, MID.
    Leveraging Mid-level Deep Representations for Prediction Face Attributes in the Wild2016Inngår i: 2016 IEEE International Conference on Image Processing (ICIP), Institute of Electrical and Electronics Engineers (IEEE), 2016Konferansepaper (Fagfellevurdert)
  • 11911.
    Zhong, Yang
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC).
    Sullivan, Josephine
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Li, Haibo
    KTH, Skolan för datavetenskap och kommunikation (CSC), Medieteknik och interaktionsdesign, MID.
    Transferring from Face Recognition to Face Attribute Prediction through Adaptive Selection of Off-the-shelf CNN RepresentationsManuskript (preprint) (Annet vitenskapelig)
  • 11912.
    Zhong, Yang
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Robotik, perception och lärande, RPL.
    Sullivan, Josephine
    KTH, Skolan för datavetenskap och kommunikation (CSC), Robotik, perception och lärande, RPL.
    Li, Haibo
    KTH, Skolan för datavetenskap och kommunikation (CSC), Medieteknik och interaktionsdesign, MID.
    Transferring from face recognition to face attribute prediction through adaptive selection of off-the-shelf CNN representations2016Inngår i: 2016 23rd International Conference on Pattern Recognition, ICPR 2016, Institute of Electrical and Electronics Engineers (IEEE), 2016, s. 2264-2269, artikkel-id 7899973Konferansepaper (Fagfellevurdert)
    Abstract [en]

    This paper addresses the problem of transferring CNNs pre-trained for face recognition to a face attribute prediction task. To transfer an off-the-shelf CNN to a novel task, a typical solution is to fine-tune the network towards the novel task. As demonstrated in the state-of-the-art face attribute prediction approach, fine-tuning the high-level CNN hidden layer by using labeled attribute data leads to significant performance improvements. In this paper, however, we tackle the same problem but through a different approach. Rather than using an end-to-end network, we select face descriptors from off-the-shelf hierarchical CNN representations for recognizing different attributes. Through such an adaptive representation selection, even without any fine-tuning, our results still outperform the state-of-the-art face attribute prediction approach on the latest large-scale dataset for an error rate reduction of more than 20%. Moreover, by using intensive empirical probes, we have identified several key factors that are significant for achieving promising face attribute prediction performance. These results attempt to gain and update our understandings of the nature of CNN features and how they can be better applied to the transferred novel tasks.

  • 11913.
    Zhou, Chenyang
    KTH, Skolan för elektroteknik och datavetenskap (EECS).
    Measure face similarity based on deep learning2019Independent thesis Advanced level (degree of Master (Two Years)), 20 poäng / 30 hpOppgave
    Abstract [en]

    Measuring face similarity is a task in computer vision that is different from face recognition. It aims to find an embedding in which similar faces have a smaller distance than dissimilar ones. This project investigates two different Siamese networks to explore whether these specific networks outperform face recognition methods on face similarity. The best accuracy is from a Siamese convolution neural network, which is 65.11%. Moreover, the best results in a similarity ranking task are obtained from Siamese geometry-aware metric learning. Besides, this project creates a novel dataset with facial image pairs for face similarity.

  • 11914. Zhou, L.
    et al.
    Schneider, F. B.
    Marsh, M. A.
    Redz, Anna
    KTH, Skolan för datavetenskap och kommunikation (CSC), Numerisk Analys och Datalogi, NADA.
    Distributed blinding for distributed ElGamal re-encryption2005Inngår i: 25th IEEE International Conference on Distributed Computing Systems, Proceedings, IEEE Computer Society, 2005, s. 815-824Konferansepaper (Fagfellevurdert)
    Abstract [en]

    A protocol is given to take an ElGamal ciphertext encrypted under the key of one distributed service and produce the corresponding ciphertext encrypted under the key of another distributed service, but without the plaintext ever becoming available. Each distributed service comprises a set of servers and employs threshold cryptography to maintain its service private key. Unlike prior work, the protocol requires no assumptions about execution speeds or message delivery delays. The protocol also imposes fewer constraints on where and when various steps are performed, which can bring improvements in end-to-end performance for some applications (e.g., a trusted publish/subscribe infrastructure.) Two new building blocks employed - a distributed blinding protocol and verifiable dual encryption proofs - could have uses beyond re-encryption protocols.

  • 11915. Zhou, Q.
    et al.
    Weinkauf, Tino
    Courant Institute, New York University.
    Sorkine, O.
    Feature-Based Mesh Editing2011Inngår i: Proceedings. Eurographics, Short Papers, 2011Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Editing and deformation of irregular meshes have become standard tools in geometric modeling. Most approaches try to preserve low-level differential properties of the surface during editing, whereas the global structure and shape of the features are not explicitly taken into account. In this paper, we introduce a feature-driven editing approach that puts global structural properties of the shape into the center of attention. We start by segmenting the mesh by ridges and valleys and use the so-defined curves and surface regions as intuitive handles for all subsequent editing operations. Our framework supports manipulations the positions and curvature values of the handles and the various mesh regions. In order to preserve the existing features, prevent unwanted appearance of new features, and maintain or manipulate global aspects of the shape, we apply curvature optimization in the affected areas. We show that the combination of feature extraction and curvature optimization leads to an intuitive modeling tool for high-quality surface manipulation.

  • 11916.
    Zhou, Tianyu
    KTH, Skolan för elektroteknik och datavetenskap (EECS).
    Deep Learning Models for Route Planning in Road Networks2018Independent thesis Advanced level (degree of Master (Two Years)), 20 poäng / 30 hpOppgave
    Abstract [en]

    Traditional shortest path algorithms can efficiently find the optimal paths in graphs using simple heuristics. However, formulating a simple heuristic is challenging under the road network setting since there are multiple factors to consider, such as road segment length, edge centrality, and speed limit. This study investigates how a neural network can learn to take these factors as inputs and yield a path given a pair of origin and destination. The research question is formulated as: Are neural networks applicable to real-time route planning tasks in a roadnetwork?. The proposed metric to evaluate the effectiveness of the neural network is arrival rate. The quality of generated paths is evaluated by time efficiency. The real-time performance of the model is also compared between pathfinding in dynamic and static graphs, using theabove metrics.

    A staggered approach is applied in progressing this investigation. The first step is to generate random graphs, which allows us to monitor the size and properties of the training graph without caring too many details in a road network. The next step is to determine, as a proof of concept, if a neural network can learn to traverse simple graphs with multiple strategies, given that road networks are in effect complex graphs. Finally, we scale up by including factors that might affect the pathfinding in real road networks. Overall, the training data is optimal paths in a graph generated by a shortest path algorithm. The model is then applied to new graphs to generate a path given a pair of origin and destination. The arrival rate and time efficiency are calculated and compared with that of the corresponding optimal path. Experimental results show that the effectiveness, i.e., arrival rate ofthe model is 90% and the path quality, i.e., time efficiency has a medianof 0.88 and a large variance. The experiment shows that the model has better performance in dynamic graphs than in static graphs. Overall, the answer to the research question is positive. However, there is still room to improve the effectiveness of the model and the paths generated by the model. This work shows that a neural network trained to make locally optimal choices can hardly give a globally optimal solution. We also show that our method, only making locally optimal choices, can adapt to dynamic graphs with little performance overhead.

  • 11917.
    Zhou, Yang
    KTH, Skolan för datavetenskap och kommunikation (CSC).
    An Implementation and Evaluation of the Least-effort Approach of Crowd Simulation2015Independent thesis Basic level (degree of Bachelor), 10 poäng / 15 hpOppgave
    Abstract [en]

    Crowd simulation serves as an important tool in architecture, where efficiency and safety could be improved with the knowledge of how large groups of people behave, and computer graphics as well as entertainment industry, where demands of animating large amounts of avatars exist. This project has implemented and evaluated an approach of crowd simulation based on the Principle of Least Effort, a fundamental rule of human behavior. The approach is capable of simulating thousands of agent in real time, and can be parallelized naturally to utilize the power of multiprocessor.

    The approach has been implemented using C++ and OpenMP. Results show that the approach generates smooth, collision-free, and visually plausible agent trajectories. To evaluate the approach in a quantitative manner, a set of metrics have been defined, and a set of test cases have been selected. By comparing the approach with RVO, a similar approach that does not consider the Principle of Least Effort, the evaluation shows that optimization based on the principle leads to agent trajectories that cost less effort and time. In further case studies, the approach has been proved to be able to generate a number of emergent phenomena verified in real crowd.

  • 11918.
    Zhu, Bin
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Medieteknik och interaktionsdesign, MID.
    Hedman, Anders
    KTH, Skolan för datavetenskap och kommunikation (CSC), Medieteknik och interaktionsdesign, MID.
    Li, Haibo
    KTH, Skolan för datavetenskap och kommunikation (CSC), Medieteknik och interaktionsdesign, MID.
    Design digital mindfulness for personal wellbeing2016Inngår i: Proceedings of the 28th Australian Computer-Human Interaction Conference, OzCHI 2016, Association for Computing Machinery, Inc , 2016, s. 626-627Konferansepaper (Fagfellevurdert)
    Abstract [en]

    The digital health and wellbeing movement has led to development of what we here baptize as digital mindfulness applications that allow people to improve psychological wellbeing. The approaches to digital mindfulness vary greatly and as a researcher it can be difficult to gain an overview of the field and what to focus on in one's own research. Here we describe four levels of digital mindfulness with examples and focus on the larger question of how to design for digital mindfulness. We end up with a set of general issues that we hope will generate further discussion and research in the field of digital mindfulness. 

  • 11919.
    Zhu, Bin
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Medieteknik och interaktionsdesign, MID. China Acad Art, Hangzhou, Zhejiang, Peoples R China..
    Hedman, Anders
    KTH, Skolan för datavetenskap och kommunikation (CSC), Medieteknik och interaktionsdesign, MID.
    Li, Haibo
    KTH, Skolan för datavetenskap och kommunikation (CSC), Medieteknik och interaktionsdesign, MID.
    Designing Digital Mindfulness: Presence-In and Presence-With versus Presence-Through2017Inngår i: PROCEEDINGS OF THE 2017 ACM SIGCHI CONFERENCE ON HUMAN FACTORS IN COMPUTING SYSTEMS (CHI'17), ASSOC COMPUTING MACHINERY , 2017, s. 2685-2695Konferansepaper (Fagfellevurdert)
    Abstract [en]

    The digital health and wellbeing movement has led to development of digital mindfulness applications that aim to help people to become mindful. In this paper we suggest a broad scheme for classifying and ordering apps intended to support mindfulness. This scheme consists of four levels of what we here term digital mindfulness. One crucial aspect of the fourth level is that artifacts at this level allow for what we term as presence-with and presence-in as opposed to presence-through, which occurs at the first three levels. We articulate our four levels along with specific design qualities through concrete examples of existing mindfulness apps and through research through design (RtD) work conducted with design fiction examples. We then use a working design case prototype to further illustrate the possibilities of presence-with and presence-in. We hope our four levels of digital mindfulness framework will be found useful by other researchers in discussing and planning the design of their own mindfulness apps and digital artifacts.

  • 11920.
    Zhu, Bin
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Medieteknik och interaktionsdesign, MID. Hubei Univ.
    Li, Haibo
    KTH, Skolan för datavetenskap och kommunikation (CSC), Medieteknik och interaktionsdesign, MID.
    Designing finger movement on mobile phone touch screen for rich emotional expression2014Inngår i: 2014 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA 2014, IEEE conference proceedings, 2014Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Emotional expression is significant as an essential part in our daily life. Ubiquitous presence of mobile technology-mediated communication creates various affective occasions and affords rich emotional expressions with lower complexity of input. In this paper, we aim to design a simple way of emotional expression through finger movements on mobile phone touch screen allowing for richer affective expressivities. We categorize the visual representations into four types according to their modality and then raised a schema that including three core properties of touch-screen based finger movement dynamics. From design practice, we find the form and property of visual representation shapes the experience of expression and the way finger moves. Kinesthetic representation with its dynamic property can reflect the core properties of finger movement and thus afford the rich expressivity in presenting emotional experience. Thus, we indicate that simple finger movements based on mobile phone touch screens can express rich emotional experience. Moreover, we suggest designing appropriate and corresponding properties of visual representation regarding to the properties of finger movement as a meaningful and expressive material. © 2014 Asia-Pacific Signal and Information Processing Ass.

  • 11921.
    Zhu, Biwen
    KTH, Skolan för elektroteknik och datavetenskap (EECS), Kommunikationssystem, CoS, Radio Systems Laboratory (RS Lab).
    Visual Tracking with Deep Learning: Automatic tracking of farm animals2018Independent thesis Advanced level (degree of Master (Two Years)), 20 poäng / 30 hpOppgave
    Abstract [en]

    Automatic tracking and video of surveillance on a farm could help to support farm management. In this project, an automated detection system is used to detect sows in surveillance videos. This system is based upon deep learning and computer vision methods. In order to minimize disk storage and to meet the network requirements necessary to achieve the real-performance, tracking in compressed video streams is essential.

    The proposed system uses a Discriminative Correlation Filter (DCF) as a classifier to detect targets. The tracking model is updated by training the classifier with online learning methods. Compression technology encodes the video data, thus reducing both the bit rates at which video signals are transmitted and helping the video transmission better adapt to the limited network bandwidth. However, compression may reduce the image quality of the videos the precision of our tracking may decrease. Hence, we conducted a performance evaluation of existing visual tracking algorithms on video sequences with quality degradation due to various compression parameters (encoders, target bitrate, rate control model, and Group of Pictures (GOP) size). The ultimate goal of video compression is to realize a tracking system with equal performance, but requiring fewer network resources.

    The proposed tracking algorithm successfully tracks each sow in consecutive frames in most cases. The performance of our tracker was benchmarked against two state-of-art tracking algorithms: Siamese Fully-Convolutional (FC) and Efficient Convolution Operators (ECO). The performance evaluation result shows our proposed tracker has similar performance to both Siamese FC and ECO.

    In comparison with the original tracker, the proposed tracker achieved similar tracking performance, while requiring much less storage and generating a lower bitrate when the video was compressed with appropriate parameters. However, the system is far slower than needed for real-time tracking due to high computational complexity; therefore, more optimal methods to update the tracking model will be needed to achieve real-time tracking.

  • 11922.
    Zhu, Di
    KTH, Skolan för informations- och kommunikationsteknik (ICT).
    Large Scale ETL Design, Optimization and Implementation Based On Spark and AWS Platform2017Independent thesis Advanced level (degree of Master (Two Years)), 20 poäng / 30 hpOppgave
    Abstract [en]

    Nowadays, the amount of data generated by users within an Internet product is increasing exponentially, for instance, clickstream for a website application from millions of users, geospatial information from GIS-based APPs of Android and IPhone, or sensor data from cars or any electronic equipment, etc. All these data may be yielded billions every day, which is not surprisingly essential that insights could be extracted or built. For instance, monitoring system, fraud detection, user behavior analysis and feature verification, etc.Nevertheless, technical issues emerge accordingly. Heterogeneity, massiveness and miscellaneous requirements for taking use of the data from different dimensions make it much harder when it comes to the design of data pipelines, transforming and persistence in data warehouse. Undeniably, there are traditional ways to build ETLs from mainframe [1], RDBMS, to MapReduce and Hive. Yet with the emergence and popularization of Spark framework and AWS, this procedure could be evolved to a more robust, efficient, less costly and easy-to-implement architecture for collecting, building dimensional models and proceeding analytics on massive data. With the advantage of being in a car transportation company, billions of user behavior events come in every day, this paper contributes to an exploratory way of building and optimizing ETL pipelines based on AWS and Spark, and compare it with current main Data pipelines from different aspects.

  • 11923.
    Zhu, Jixiang
    KTH, Skolan för informations- och kommunikationsteknik (ICT).
    Computation Offloading and Task Scheduling among Multi-Robot Systems2017Independent thesis Advanced level (degree of Master (Two Years)), 20 poäng / 30 hpOppgave
    Abstract [en]

    In a Multi-Robot System (MRS), robots perform some collaborative behaviors so that some goals that are impossible for a single robot to achieve become feasible and attainable. Developing rapidly and exploited widely, cloud further extends the resources a robot can access thereby bringing significant potential benefits to robotic and automation systems. One of the potential benefits is Computation Offloading that moves the computational heavily parts of an application onto a server to reduce the execution time. However, to enable the computation offloading, the question must be answered when, what, where and how to offload? While some offloading mechanisms proposed in the mobile computing area (i.e., smartphones, pads), the question remains not fully answered and many new challenges emerge when it comes to the robotic realm.

    This paper aims to apply computation offloading technology to a Multi-Robot System and investigate the performance impact it has on the processing time of robot applications. For this purpose, a computation offloading framework is proposed for an elastic computing model with the engagement of a two-tier cloud infrastructure, i.e., a public cloud infrastructure and an ad-hoc local network (fog) formed by a cluster of robots. Two scheduling algorithms: Heterogeneous-Earliest-Finish-Time (HEFT) and Critical-Path-on-a-Processor (CPOP) are implemented to schedule the offloaded tasks to available robots and servers such that the total execution time of the application is minimized. The offloading framework is implemented based on Robot Operating System (ROS) and tested through simulated applications. The results prove the feasibility of proposed offloading framework and indicate potential execution speeding up of robot applications by exploiting offloading technology.

  • 11924.
    Zhu, Jun
    KTH, Skolan för informations- och kommunikationsteknik (ICT), Elektronik- och datorsystem, ECS.
    Energy and Design Cost Efficiency for Streaming Applications on Systems-on-Chip2009Licentiatavhandling, monografi (Annet vitenskapelig)
    Abstract [en]

    With the increasing capacity of today's integrated circuits, a number ofheterogeneous  system-on-chip (SoC)  architectures  in embedded  systemshave been proposed. In order to achieve energy and design cost efficientstreaming applications  on these  systems, new design  space explorationframeworks  and  performance  analysis  approaches are  required.   Thisthesis  considers three state-of-the-art  SoCs architectures,  i.e., themulti-processor SoCs (MPSoCs)  with network-on-chip (NoC) communication,the hybrid CPU/FPGA architectures, and the run-time reconfigurable (RTR)FPGAs.  The main topic of the  author?s research is to model and capturethe  application  scheduling,  architecture  customization,  and  bufferdimensioning  problems, according to  the real-time  requirement.  Sincethese  problems  are NP-complete,  heuristic  algorithms and  constraintprogramming solver are used to compute a solution.For  NoC  communication  based  MPSoCs,  an  approach  to  optimize  thereal-time    streaming    applications    with   customized    processorvoltage-frequency levels and memory  sizes is presented. A multi-clockedsynchronous  model  of  computation   (MoC)  framework  is  proposed  inheterogeneous  timing analysis and  energy estimation.   Using heuristicsearching  (i.e., greedy  and  taboo search),  the  experiments show  anenergy reduction (up to 21%)  without any loss in application throughputcompared with an ad-hoc approach.On hybrid CPU/FPGA architectures,  the buffer minimization scheduling ofreal-time streaming  applications is addressed.  Based  on event models,the  problem  has  been  formalized  decoratively  as  constraint  basescheduling,  and  solved  by  public domain  constraint  solver  Gecode.Compared  with  traditional  PAPS  method,  the  proposed  method  needssignificantly smaller  buffers (2.4%  of PAPS in  the best  case), whilehigh throughput guarantees can still be achieved.Furthermore, a  novel compile-time analysis approach  based on iterativetiming  phases is  proposed  for run-time  reconfigurations in  adaptivereal-time   streaming   applications  on   RTR   FPGAs.   Finally,   thereconfigurations analysis and design trade-offs analysis capabilities ofthe proposed  framework have been  exemplified with experiments  on bothexample and industrial applications.

  • 11925.
    Zhu, Jun
    KTH, Skolan för informations- och kommunikationsteknik (ICT), Elektroniksystem.
    Performance Analysis and Implementationof Predictable Streaming Applications onMultiprocessor Systems-on-Chip2010Doktoravhandling, monografi (Annet vitenskapelig)
    Abstract [en]

    Driven by the increasing capacity of integrated circuits, multiprocessorsystems-on-chip (MPSoCs) are widely used in modern consumer electron-ics devices. In this thesis, the performance analysis and implementationmethodologies are explored to design predictable streaming applications onMPSoCs computing platforms. The application functionality and concur-rency are described in synchronous data flow (SDF) computational models,and two state-of-the-art architecture templates are adopted as multiproces-sor architectures, i.e., network-on-chip (NoC) based MPSoC and hybrid re-configurable CPU/FPGA platforms. Based on the author’s contributions onsimulation and formal analytical methods, performance analysis and designspace exploration for embedded MPSoCs architectures have been addressed.

    An energy efficient design space exploration flow is proposed for stream-ing applications with guaranteed throughput on NoC based MPSoCs, in whichboth application throughput analysis and system energy calculation are car-ried out by simulation on a multi-clocked synchronous modelling frame-work. On the other hand, based on event models of data streams, a formalanalytical scheduling framework for real-time streaming applications withminimal buffer requirement on hybrid CPU/FPGA architectures is exploited.The scheduling problem has been formalized declaratively by constraint basetechniques, and solved by a public domain constraint solver. Consecutively,the constraint based method has been extended to solve problems rangingfrom global computation/communication scheduling and reconfiguration anal-ysis to Pareto efficient design. Finally, a prototype of stream processing sys-tem on FPGA based MPSoC is built to substantiate the results from theoreti-cal studies in this thesis.

  • 11926.
    Zhu, Jun
    et al.
    KTH, Skolan för informations- och kommunikationsteknik (ICT), Elektronik- och datorsystem, ECS.
    Sander, Ingo
    KTH, Skolan för informations- och kommunikationsteknik (ICT), Elektronik- och datorsystem, ECS.
    Jantsch, Axel
    KTH, Skolan för informations- och kommunikationsteknik (ICT), Elektronik- och datorsystem, ECS.
    Buffer Minimization of Real-Time Streaming Applications Scheduling on Hybrid CPU/FPGA Architectures2009Inngår i: DATE: 2009 DESIGN, AUTOMATION & TEST IN EUROPE CONFERENCE & EXHIBITION, 2009, s. 1506-1511Konferansepaper (Fagfellevurdert)
    Abstract [en]

    We address the problem of real-time streaming applications scheduling on hybrid CPU/FPGA architectures. The main contribution is a two-step approach to minimize the buffer requirement for streaming applications with throughput guarantees. A novel declarative way of constraint based scheduling for real-time hybrid SW/HW systems is proposed, while the application throughput is guaranteed by periodic phases in execution. We use a voice-band modem application to exemplify the scheduling capabilities of our method. The experimental results show the advantages of our techniques in both less buffer requirement and higher throughput guarantees compared to the traditional PAPS method.

  • 11927.
    Zhu, Jun
    et al.
    KTH, Skolan för informations- och kommunikationsteknik (ICT), Elektroniksystem.
    Sander, Ingo
    KTH, Skolan för informations- och kommunikationsteknik (ICT), Elektroniksystem.
    Jantsch, Axel
    KTH, Skolan för informations- och kommunikationsteknik (ICT), Elektroniksystem.
    Constrained Global Scheduling of Streaming Applications on MPSoCs2010Inngår i: 2010 15TH ASIA AND SOUTH PACIFIC DESIGN AUTOMATION CONFERENCE (ASP-DAC 2010), 2010, s. 223-228Konferansepaper (Fagfellevurdert)
    Abstract [en]

    We present a global scheduling framework for synchronous data flow (SDF) streaming applications on MPSoCs, based on optimized computation and contention-free routing. The global scheduling of processors computing and communication transactions are formulated as constraint based problem, to avoid the scheduling overhead in TDMA-like heuristic schemes. A public domain constraint solver is exploited to solve the NP-complete scheduling efficiently, together with problem specific constraint modeling techniques. Experimental results show that the proposed framework can achieve a high predictable application throughput with minimized buffer cost. For instance, for applications in communication domain, higher throughput (up to 87%) has been observed with less buffer cost, compared to scenarios considering the heuristic scheduling overhead.

  • 11928.
    Zhu, Jun
    et al.
    KTH, Skolan för informations- och kommunikationsteknik (ICT), Elektronik- och datorsystem, ECS.
    Sander, Ingo
    KTH, Skolan för informations- och kommunikationsteknik (ICT), Elektronik- och datorsystem, ECS.
    Jantsch, Axel
    KTH, Skolan för informations- och kommunikationsteknik (ICT), Elektronik- och datorsystem, ECS.
    Performance Analysis of Reconfiguration in Adaptive Real-Time Streaming Applications2008Inngår i: PROCEEDINGS OF THE 2008 IEEE/ACM/IFIP WORKSHOP ON EMBEDDED SYSTEMS FOR REAL-TIME MULTIMEDIA / [ed] Eles P; Pimentel AD, 2008, s. 53-58Konferansepaper (Fagfellevurdert)
    Abstract [en]

    We propose a design optimization framework for adaptive real-time streaming applications. The main contribution is a hybrid approach for performance analysis combining formal analysis and simulation using a two-phase framework. We formulate the scheduling problem of adaptive streaming applications with ILP analysis, and use the simulation based on the synchronous model of computation to ensure throughput guarantees. We finally illustrate the capabilities of our methodology by experiments.

  • 11929.
    Zhu, Lei
    KTH, Skolan för informations- och kommunikationsteknik (ICT).
    Security Extensions of the OpenStack Platform2013Independent thesis Advanced level (degree of Master (Two Years)), 20 poäng / 30 hpOppgave
    Abstract [en]

    The emergence of Cloud Computing has become one of hottest topics in IT industry. So, what is cloud computing? There are many definitions summarized by people from different areas in their perspectives. However, the US National Institute of Standard Technology (NIST) [1] defines cloud computing as a model for enabling ubiquitous, convenient, ondemand network access to a shared pool of configurable computing resources (e.g., networks, servers, storage, applications, and services) [2].

    Despite of all the benefits that Cloud Computing brings to the IT industry, there are increasing issues being pointed out about the security and privacy due to the currently immature cloud security status. NIST points out that there are several security and privacy issues in the area of public cloud computing including governance, authentication, access control, data protection and availability [3].

    This master thesis is intended to build security architecture for open-source cloud computing platform. This thesis work concentrates on providing strong authentication service between cloud provider and users, as well as delivering access control and Single- Sign-On (SSO) service to the users, which are provided by the central security system. The central security system, as the proposed solution for secure cloud-computing platform, comprises of different security components providing security services in the form of web services. OpenStack as an open-source cloud-computing platform is chose for the research.

  • 11930.
    Zhu, Lin
    KTH, Skolan för informations- och kommunikationsteknik (ICT).
    DESIGN AND IMPLEMENTATION A BATTERY MANAGEMENT SYSTEM FOR A MULTI‐FUNCTION POWER CONVERTER2014Independent thesis Advanced level (degree of Master (Two Years)), 20 poäng / 30 hpOppgave
    Abstract [en]

    This thesis work designed and implemented an advanced Battery Management System (BMS) for a battery package with 96 Lithium-ion battery cells connected in series. The focus of this thesis placed on battery model building, battery balancing algorithm developing, State-of-Charge (SOC) estimation algorithm developing, and implementing software in microprocessor.A set of simulation program is developed to verify the battery model and the algorithms. A battery simulator based on SPICE is built to implement a first order Thevenin dynamic electrochemical model. PID control algorithm is employed in balancing the battery cells. Meanwhile, Extended Kalman Filter (EKF) algorithm is used for estimating the SOC. An interactive web GUI application is also developed for easy control. Software running on STM32F103 microprocessor has been developed to adapt the existing BMS hardware.The simulation result proves that the first order Thevenin dynamic electrochemical model reflect the behavior of a real battery accurately, the PID balancing algorithm is effective to make the battery cells stay in balanced state and the error of EKF SOC estimation algorithm is below 5%.

  • 11931.
    Zhu, Rui
    et al.
    KTH, Skolan för arkitektur och samhällsbyggnad (ABE), Samhällsplanering och miljö, Geodesi och geoinformatik.
    Gidofalvi, Gyözö
    KTH, Skolan för arkitektur och samhällsbyggnad (ABE), Samhällsplanering och miljö, Geodesi och geoinformatik.
    GPS-based Crowd Sourced Intelligent Traffic Information Hub2013Inngår i: Proceedings of the 26th International Cartographic Conference / [ed] Manfred F. Buchroithner, ICC International Cartographic Association , 2013, s. 669-670Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Congestion is a major problem in most metropolitan areas and given the increasing rate of urbanization it is likely to be an even more serious problem in the rapidly expanding mega cities. Some well know negative effects of congestion include: 1) the economic losses and quality of life degradation that result from the increased and unpredictable travel times, 2) the increased level of carbon footprint that vehicles idling in congestions leave behind, and 3) the increased number of traffic accidents that are direct results of the stress and fatigue of drivers that are stuck in congestion.

    One possible method to combat congestion is provide intelligent traffic management systems that can in a timely manner inform drivers about current or predicted traffic congestion that is relevant to them on their journeys. This this extent, the present paper proposes a scalable, grid-based intelligent traffic information hub that facilitates the manual definition and/or automatic detection of abnormal traffic condition events, e.g., accidents or congestion, and in advance informs drivers about events that will likely be relevant to them on their journey, thereby allowing the divers or their onboard navigation units to alter their paths as needed.

    The proposed system achieves the above described functionality through the following methodology. The system, without loss of generality, adopts a grid-based discretization of space, which by changing the resolution of the grid allows the system to scale in terms of it computation cost and the geographical level of detail of traffic information that it manages. The system derives traffic information from the continuous stream of grid-based position and speed reports that it receives from the vehicles. In particular, the system in an online fashion 1) summarizes Current (grid-based) Traffic Flow Statistics (CTFS), i.e., it records for each grid cell g from each neighboring grid cell n, the mean and standard deviation of the speeds of the vehicles that are currently located in g and have entered g from n; and 2) efficiently incorporates the CTFS into compressed Historical (grid-based) Traffic Flow Statistics (HTFS) using incremental statistics. Simultaneously, using a sliding window model, the system also 1) maintains the Recent (grid-based) Trajectories (RT) of the vehicles; 2) extracts Recent (gridbased) Mobility Statistics (RMS), i.e., it records for each destination grid cell d, for each neighboring grid cell n of g, and for each possible source grid cell s, the number of vehicles that (i) are currently in d, (ii) have entered d from n, and (iii) have a RT that has passed through s; and 3) efficiently incorporates the RMS into compressed Historical (grid-based) Mobility Statistics (HMS) using incremental statistics. To capture the temporal variability in traffic flow and mobility patterns at different scales, the system through temporal domain projections maintains day-of-week and hour-ofday based aggregations of HTFS and RMS. Then, the system classifies a grid cell g to be congested from the direction of a neighboring grid cell n if the current mean speed of vehicles that entered the grid cell g from the direction of n is below the normal according to the temporally relevant HFS. Finally, based on the temporally relevant HMS, the system sends out congestion notifications to vehicles that are likely to be effected in the future part of their journey by these congestions, i.e., the system sends out a congestion notification (g,n) to a vehicle v that is currently located in some grid cell s from which the likelihood of v moving to g through n within the prediction horizon is above a user-defined threshold.

    Extensive empirical evaluations on large sets of realistically simulated trajectories of vehicles illustrate that the above described methodology and its simple SQL-based implementation in a relational database system is scalable and effective. In particular, the execution time of- and the space used by the system scales linearly with the input size (number of concurrently moving vehicles) and the method’s mutually dependent parameters (grid resolution r and RT length l) that jointly define a spatio-temporal resolution. Within the area of a large city (40km by 40km), assuming a 60km/h average vehicle speed, the system, running on a single personal computer, can manage the described congestion detection and one-minute-ahead notification tasks within real-time requirements for 15 thousand and 2.5 million concurrently moving vehicles for spatio-temporal resolutions (r=62.5m, l=17) and (r=4km,l=2), respectively. Finally, the proposed method, for all spatio-temporal resolutions and prediction horizons, significantly outperforms in terms of notification accuracy the grid-based baseline method, which sends non-directional congestion notifications based on the recent linear movement tendencies of vehicles. 

  • 11932.
    Ziadi, Ahmed
    KTH, Skolan för datavetenskap och kommunikation (CSC).
    Facebook som komplement till modersmålsundervisning2014Independent thesis Basic level (degree of Bachelor), 10 poäng / 15 hpOppgave
    Abstract [en]

    Facebook is the most widely used social media in Sweden. It allows the user to easily share the latest from their everyday life, their opinions, as well as communicate with their acquaintances. According to the latest poll from the Foundation for Internet Infrastructure, 33% of teenagers in the ages 12-15 spend their Internet time being active on social media. 63% of these teenagers visit Facebook on daily basis.

    Herein, we examined how Facebook can be exploited as a complement to the education of the mother tongue. The investigation was performed with a questionnaire as well as a test group that has been supplemented with semi-structured interviews. 

    In conclusion, the study showed promising results in the usage of Facebook with the education. By taking parts in discussions on Facebook, the students did not only improve their discussion abilities but also the writing. It was also observed that the communication between student and teacher was greatly improved. A remarkable observation was that students grown up in Sweden were more in favour for the use of Facebook as an educational tool than students grown up outside of Sweden.

  • 11933.
    Zikopi, Eleni
    KTH, Skolan för elektroteknik och datavetenskap (EECS).
    A case study research on Scrum Framework2019Independent thesis Advanced level (degree of Master (Two Years)), 20 poäng / 30 hpOppgave
    Abstract [en]

    Agile methods have been widely implemented in the industry while teaching these methods is a substantial part of Computer Science and Engineering program curricula. Evidencedriven data of agile practices, methods, and tools have been extracted based on empirical studies with students, however, there is an important need for more anecdotal evidence to confirm these findings. In order to fill this gap, this paper explores the perceptions and the applicability of the Scrum Framework in a student research team in an industrial context. Empirical data have been gathered through interviews with the case study participants combined with a survey. The analysis reveals that student experiences are mainly positive and that they can easily grasp the benefits of Scrum Framework. The challenges of implementing Scrum in such a setting mainly concern the balance between coach and self-organization, formulating accurate user stories when researching, finding the most suitable estimation method, as well as planning when conducting research. The empirical findings may potentially be extrapolated in student scrum teams or even in industrial settings. Finally, this research paper should encourage other researchers to investigate the adoption of Scrum in a student setting.

  • 11934.
    Zikou, Filippia
    KTH, Skolan för informations- och kommunikationsteknik (ICT).
    Tweetopolitics: A Scalable Platform for Analyzing Swedish Elections on Twitter2015Independent thesis Advanced level (degree of Master (Two Years)), 20 poäng / 30 hpOppgave
    Abstract [en]

    Due to its real-time, open and democratic nature in information dissemination Twitter has become a common-ground for civic opinion expression as well as observation. This is much anticipated on the wake of an electoral event. As a result, politicians spend considerable amount of resources on analyzing the positive and negative opinions shared with respect to their orientation. Ultimately they become keen on leveraging their popularity to increase their followers base through social media. This is where user profiling and recommendation systems become useful by eliciting social preferences of political parties and their respective followers, and leveraging such intelligence to suggest relevant parties to the interested followers. To this end, we present results of applying our user profiling approach on a Twitter dataset focus-crawled during the course of 2014 general elections of Sweden. Results of analyzing content of tweets show how parties speak of controversial topics, while results of network mining show how much interactions and popularities of the parties change during the month of Election.

  • 11935.
    Zimmer, Michael
    et al.
    University of California, Berkeley.
    Broman, David
    University of California, Berkeley and Linköping University.
    Shaver, Chris
    University of California, Berkeley.
    Lee, Edward A.
    University of California, Berkeley.
    FlexPRET: A Processor Platform for Mixed-Criticality Systems2014Inngår i: Proceedings of the 20th IEEE Real-Time and Embedded Technology and Application Symposium (RTAS), IEEE conference proceedings, 2014, s. 101-110Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Mixed-criticality systems, in which multiple tasks of varying criticality execute on a single hardware platform, are an emerging research area in real-time embedded systems. High-criticality tasks require spatial and temporal isolation guarantees for independent verification, and the task set should efficiently utilize hardware resources. Hardware-based isolation is desirable but often underutilizes hardware resources, which can consist of multiple single-core, multicore, or multithreaded processors. We present FlexPRET, a processor designed specifically for mixed-criticality systems by allowing each task to make a trade-off between hardware-based isolation and efficient processor utilization. FlexPRET uses fine-grained multithreading with flexible scheduling and timing instructions to provide this functionality.

  • 11936. Zivkovic, Zoran
    et al.
    Booij, Olaf
    Kröse, Ben
    Topp, Elin Anna
    KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    Christensen, Henrik I.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS.
    From sensors to human spatial concepts: An annotated data set2008Inngår i: IEEE Transactions on Robotics, ISSN 1552-3098, Vol. 24, nr 2, s. 501-505Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    An annotated data set is presented meant to help researchers in developing, evaluating, and comparing various approaches in robotics for building space representations appropriate for communicating with humans. The data consist of omnidirectional images, laser range scans, sonar readings, and robot odometry. A set of base-level human spatial concepts is used to annotate the data.

  • 11937. Zois, D. -S
    et al.
    Levorato, Marco
    KTH, Skolan för elektro- och systemteknik (EES), Reglerteknik. KTH, Skolan för elektro- och systemteknik (EES), Centra, ACCESS Linnaeus Centre.
    Mitra, U.
    Non-linear smoothers for discrete-time, finite-state Markov chains2013Inngår i: IEEE International Symposium on Information Theory: Proceedings, 2013, s. 2099-2103Konferansepaper (Fagfellevurdert)
    Abstract [en]

    The problem of enhancing the quality of system state estimates is considered for a special class of dynamical systems. Specifically, a system characterized by a discrete-time, finite-state Markov chain state and observed via conditionally Gaussian measurements is assumed. The associated mean vectors and covariance matrices are tightly intertwined with the system state and a control input selected by a controller. Exploiting an innovations approach, finite-dimensional, non-linear approximate MMSE smoothing estimators are derived for the Markov chain system state. The resulting smoothers are driven by a control policy determined by a stochastic dynamic programming algorithm, which minimizes the MSE filtering error, and was proposed in our earlier work. An application of the smoothers derived in this paper is presented for the problem of physical activity detection in wireless body sensing networks, which illustrates the performance enhancement due to smoothing.

  • 11938.
    Zomer, Lara-Britt
    et al.
    KTH, Skolan för teknik och hälsa (STH).
    Moustaid, Elhabib
    KTH, Skolan för teknik och hälsa (STH).
    Meijer, Sebastiaan
    KTH, Skolan för teknik och hälsa (STH).
    A META-MODEL FOR INCLUDING SOCIAL BEHAVIOR AND DATA INTO SMART CITY MANAGEMENT SIMULATIONS2015Inngår i: 2015 WINTER SIMULATION CONFERENCE (WSC), IEEE , 2015, s. 1705-1716Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Smart city management can be regarded to bridge different realms of thinking about cities, i.e. 1) the city as complex-adaptive system, 2) socio-technical operational control center and 3) multi-actor policy-making. Underpinned by different world views and theoretical bodies, integration of the three realms puts forward new demands on simulation approaches and challenges current knowledge and available technology regarding integration of sub-models across different systems. In order to support urban transportation management, a holistic approach is needed that semantically connects the three realms by incorporation of human behavior and knowledge. Combining research on knowledge management and computer science, this paper presents a novel meta-framework as socio-technical hybrid simulation language to generalize integration of simulations, gaming and data for modeling urban transportation.

  • 11939.
    Zou, Zhuo
    et al.
    KTH, Skolan för informations- och kommunikationsteknik (ICT), Centra, VinnExcellence Center for Intelligence in Paper and Packaging, iPACK. KTH, Skolan för informations- och kommunikationsteknik (ICT), Elektronik- och datorsystem, ECS.
    Ruan, Yue
    KTH, Skolan för informations- och kommunikationsteknik (ICT), Centra, VinnExcellence Center for Intelligence in Paper and Packaging, iPACK. KTH, Skolan för informations- och kommunikationsteknik (ICT), Elektronik- och datorsystem, ECS.
    Zheng, Li-Rong
    KTH, Skolan för informations- och kommunikationsteknik (ICT), Centra, VinnExcellence Center for Intelligence in Paper and Packaging, iPACK. KTH, Skolan för informations- och kommunikationsteknik (ICT), Elektronik- och datorsystem, ECS.
    Tenhunen, Hannu
    KTH, Skolan för informations- och kommunikationsteknik (ICT), Centra, VinnExcellence Center for Intelligence in Paper and Packaging, iPACK. KTH, Skolan för informations- och kommunikationsteknik (ICT), Elektronik- och datorsystem, ECS.
    Impulse UWB Energy Detection Receiver with Energy Offset Synchronization Scheme2009Inngår i: 2009 IEEE INTERNATIONAL CONFERENCE ON ULTRA-WIDEBAND (ICUWB 2009), NEW YORK: IEEE , 2009, s. 540-544Konferansepaper (Fagfellevurdert)
    Abstract [en]

    Impulse ultra-wideband radios (IR-UWB) show strong advantages in low power and low cost applications such as RFIDs and wireless sensor networks. This paper presents an IR-UWB receiver based on Energy Detection (ED) with on-off keying (OOK) modulation. A novel synchronization and detection algorithm using the energy offset scheme with adaptive threshold detection is suggested, aiming to reduce energy consumption and simplify hardware complexity. Simulation and FPGA implementation reveal that the proposed method can avoid complex and power consuming synchronization blocks, and reduce the preamble length, whereas maintaining the performance in the target level. Hardware integration issues are discussed, implying that the proposed receiver architecture has the possibility to achieve low complexity and low power implementation with several nJs energy per bit, at a data rate of 10Mb/s.

  • 11940.
    Zsiga, Bálint
    KTH, Skolan för informations- och kommunikationsteknik (ICT).
    Gambiance: EXPLORING NEW ROLES OF LIGHT IN BOARD GAMES BEYOND ILLUMINATION2015Independent thesis Advanced level (degree of Master (Two Years)), 20 poäng / 30 hpOppgave
    Abstract [en]

    In this thesis we will present a study on using lighting to enhance the gameplay of modern board games. Informed by observing board gaming events and getting engaged on forums we learned that besides debating strategies and the game mechanics, another regular discussion is on how to create good environments for games and playing. Based on our findings we frame the design space of light extended board games and propose three types of roles that lighting could play in board games to enhance the gameplay experience: (1) ambiance support for decorative purposes, eg. creating thematic atmosphere, (2) gameplay elements like thematic timers, and (3) game tools such as lighting objects that players can interact with.

    We designed a light extended board game prototype in order to evaluate several ambiance support and gameplay element role concepts. A Wizard-of-Oz test verified that players experience an enhanced focus using the light extended game. On the other hand, some ambiance support also distracted players. Thematic indications enhance sensory immersion, and randomly triggered elements can make the game more exciting by causing surprise and uncertainty, while reducing player e↵ort. Finally, we conclude this thesis by discussing results and outlining future work.

  • 11941.
    Zucchelli, Marco
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.
    Kosecka, Jana
    Motion bias and structure distortion induced by intrinsic calibration errors2008Inngår i: Image and Vision Computing, ISSN 0262-8856, E-ISSN 1872-8138, Vol. 26, nr 5, s. 639-646Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    This article provides an account of sensitivity and robustness of structure and motion recovery with respect to the errors in intrinsic parameters of the camera. We demonstrate both analytically and in simulation, the interplay between measurement and calibration errors and their effect on motion and structure estimates. In particular we show that the calibration errors introduce an additional bias towards the optical axis, which has opposite sign to the bias typically observed by egomotion algorithms. The overall bias causes a distortion of the resulting 3D structure, which we express in a parametric form. The analysis and experiments are carried out in the differential setting for motion and structure estimation from image velocities. While the analytical explanations are derived in the context of linear techniques for motion estimation, we verify our observations experimentally on a variety of optimal and suboptimal motion and structure estimation algorithms. The obtained results illuminate and explain the performance and sensitivity of the differential structure and motion recovery techniques in the presence of calibration errors.

  • 11942. Zudilova-Seinstra, E.V.
    et al.
    Yang, N.
    Axner, Lilit
    Section Computational Science, Informatics Institute, University of Amsterdam.
    Wibisono, A.
    Vasunin, V.
    Service-Oriented Visualization applied to Medical Data Analysis2008Inngår i: Service Oriented Computing and Applications, ISSN 1863-2386, E-ISSN 1863-2394, Vol. 2, nr 4, s. 187-201Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    With the era of Grid computing, data driven experiments and simulations have become very advanced and complicated. To allow specialists from various domains to deal with large datasets, aside from developing efficient extraction techniques, it is necessary to have available computational facilities to visualize and interact with the results of an extraction process. Having this in mind, we developed an Interactive Visualization Framework, which supports a service-oriented architecture. This framework allows, on one hand visualization experts to construct visualizations to view and interact with large datasets, and on the other hand end-users (e.g., medical specialists) to explore these visualizations irrespective of their geographical location and available computing resources. The image-based analysis of vascular disorders served as a case study for this project. The paper presents main research findings and reports on the current implementation status.

  • 11943. Zulkafli, Zed
    et al.
    Perez, Katya
    Vitolo, Claudia
    Buytaert, Wouter
    Karpouzoglou, Timothy
    Public Administration and Policy Group, Wageningen University, Netherlands.
    Dewulf, Art
    De Bièvre, Bert
    Clark, Julian
    Hannah, David M.
    Shaheed, Simrita
    User-driven design of decision support systems for polycentric environmental resources management2017Inngår i: Environmental Modelling & Software, ISSN 1364-8152, E-ISSN 1873-6726, Vol. 88, s. 58-73Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Open and decentralized technologies such as the Internet provide increasing opportunities to create knowledge and deliver computer-based decision support for multiple types of users across scales. However, environmental decision support systems/tools (henceforth EDSS) are often strongly science-driven and assuming single types of decision makers, and hence poorly suited for more decentralized and polycentric decision making contexts. In such contexts, EDSS need to be tailored to meet diverse user requirements to ensure that it provides useful (relevant), usable (intuitive), and exchangeable (institutionally unobstructed) information for decision support for different types of actors. To address these issues, we present a participatory framework for designing EDSS that emphasizes a more complete understanding of the decision making structures and iterative design of the user interface. We illustrate the application of the framework through a case study within the context of water-stressed upstream/downstream communities in Lima, Peru.

  • 11944.
    Álvarez Álvarez, Òscar
    KTH, Skolan för informations- och kommunikationsteknik (ICT).
    Business transformation based on ICT: Smart Grid2014Independent thesis Advanced level (degree of Master (Two Years)), 20 poäng / 30 hpOppgave
    Abstract [en]

    During the recent years several technologies and services based in Internet of Things (IoT) and Machine-to-Machine communications (M2M) have appeared in many different sectors; where IoT can be defined as the idea that any device that can be benefited by being connected will be connected and M2M communications is defined as the kind of communication between devices with minimal human interaction. IoT and M2M solutions can be applied in many sectors, like healthcare, transport, logistics, media or utilities. In every sector the motivations to implement this new services is different, as each sector has different final objectives and different actors and business models.

    When new technologies (like Smart Grid) appear two types of challenges can be defined: technical and business challenges, therefore innovation has to be applied in both of them. Too often innovation is focus on the technologic evolution and underestimated on the business field, however it is a key aspect for new technologies and services to reach commercial success.

    From the technological point of view the state of research on Smart Grid applications and services is quite advanced, while authors consider that innovation in the business part is one of the biggest challenges for Smart Grid technologies to reach success. The goal of this project is to understand the Smart Grid environment and context in different countries and propose business models suitable for the Smart Grid environment.

  • 11945.
    Ähdel, Victor
    KTH, Skolan för elektroteknik och datavetenskap (EECS).
    On the effect of architecture on deep learning based features for homography estimation2018Independent thesis Advanced level (degree of Master (Two Years)), 20 poäng / 30 hpOppgave
    Abstract [en]

    Keypoint detection and description is the first step of homography and essential matrix estimation, which in turn is used in Visual Odometry and Visual SLAM. This work explores the effect (in terms of speed and accuracy) of using different deep learning architectures for such keypoints. The fully convolutional networks — with heads for both the detector and descriptor — are trained through an existing self-supervised method, where correspondences are obtained through known randomly sampled homographies. A new strategy for choosing negative correspondences for the descriptor loss is presented, which enables more flexibility in the architecture design. The new strategy turns out to be essential as it enables networks that outperform the learnt baseline at no cost in inference time.

    Varying the model size leads to a trade-off in speed and accuracy, and while all models outperform ORB in homography estimation, only the larger models approach SIFT’s performance; performing about 1-7% worse. Training for longer and with additional types of data might give the push needed to outperform SIFT. While the smallest models are 3× faster and use 50× fewer parameters than the learnt baseline, they still require 3× as much time as SIFT while performing about 10-30% worse. However, there is still room for improvement through optimization methods that go beyond architecture modification, e.g. quantization, which might make the method faster than SIFT.

  • 11946.
    Älvenstrand, Daniel
    et al.
    KTH, Skolan för teknikvetenskaplig kommunikation och lärande (ECE).
    Horna, Joakim
    KTH, Skolan för teknikvetenskaplig kommunikation och lärande (ECE).
    Lärande inom vården – Ett digitalt frö: En pilotstudie i att designa ett nätbaserat lärverktyg för att effektivisera introduktionsutbildningen för sjuksköterskor inom hematologi.2015Independent thesis Advanced level (professional degree), 20 poäng / 30 hpOppgave
    Abstract [sv]

    I dagsläget är introduktionsutbildningen för sjuksköterskorna på kliniken för hematologi på Karolinska Universitetssjukhuset otillräcklig vilket kan bidra till en äventyrad patientsäkerhet. Kliniken hoppas på att, med hjälp av ett interaktivt nätbaserat lärverktyg, kunna effektivisera sjuksköterskornas interna utbildning, göra deras utbildningsmaterial lättare att lära och motivera dem till fortsatt lärande.

     

    Detta examensarbete undersökte huruvida klinikens förhoppningar kunde uppnås. Detta undersöktes genom att skapa och utvärdera en prototyp till ett lärverktyg. Genom att kombinera teorier och forskning kring nätbaserad utbildning, användarcentrerad design, interaktionsdesign och lärandeperspektiv utvecklades ett prototypverktyg för nätbaserat lärande.

     

    För att identifiera sjuksköterskornas behov och situation gjordes en förstudie i form av en enkät- och intervjuundersökning på klinikens personal samt en intervjustudie med ansvarig personal på kliniken och sjukhuset. En prototyp av verktyget utvecklades och dess användbarhet utvärderades tillsammans med sjuksköterskorna. Verktyget utvärderades även gällande hur det kunde effektivisera lärandet av det utbildningsmaterial inom cytostatika som tillhandahålls av landstinget; detta genom utformandet och testandet av en kurs.

     

    Examensarbetets resultat identifierar de faktorer som bidrar till att göra ett nätbaserat lärverktyg användbart för klinikens personal. Dessa faktorer, tillsammans med identifierandet av de faktorer som påverkar deras lärandeprocess, bidrar till att effektivisera sjuksköterskornas introduktionsutbildning. Som slutsats kan ett lärverktyg som utvecklas tillsammans med berörd personal enligt en kombination av design- och lärandeperspektiv göras användbart och utbildande för att säkerställa sjuksköterskornas kompetenser och bidra till en ökad patientsäkerhet.

  • 11947.
    Åberg, Ludvig
    KTH, Skolan för elektroteknik och datavetenskap (EECS).
    Multimodal Classification of Second-Hand E-Commerce Ads2018Independent thesis Advanced level (degree of Master (Two Years)), 20 poäng / 30 hpOppgave
    Abstract [en]

    In second-hand e-commerce, categorization of new products is typically done by the seller. Automating this process makes it easier to upload ads and could lower the number of incorrectly categorized ads. Automatic ad categorization also makes it possible for a second-hand e-commerce platform to use a more detailed category system, which could make the shopping experience better for potential buyers. Product ad categorization is typically addressed as a text classification problem as most metadata associated with products are textual. By including image information, i.e. using a multimodal approach, better performance can however be expected. The work done in this thesis evaluates different multimodal deep learning models for the task of ad categorization on data from Blocket.se. We examine late fusion models, where the modalities are combined at decision level, and early fusion models, where the modalities are combined at feature level. We also introduce our own approach Text Based Visual Attention  (TBVA), which extends the image CNN Inception v3 with an attention mechanism to incorporate textual information. For all models evaluated, the text classifier fastText is used to process text data and the Inception v3 network to process image data. Our results show that the late fusion models perform best in our setting. We conclude that these models generally learn which of the baseline models to ’trust’, while early fusion and the TBVA models learn more abstract concepts. As future work, we would like to examine how the TBVA models perform on other tasks, such as ad similarity.

  • 11948.
    Åberg, Måns
    et al.
    KTH, Skolan för datavetenskap och kommunikation (CSC).
    Fridh, Gustav
    KTH, Skolan för datavetenskap och kommunikation (CSC).
    Plattformsbaserat samarbete inom matematik2015Independent thesis Basic level (degree of Bachelor), 10 poäng / 15 hpOppgave
    Abstract [sv]

    Matematikkurser på Kungliga Tekniska Högskolan läses varje år av flera tusen studenter. Genomströmningen är låg relativt andra kurser och att öka andelen studenter som klarar kurserna utan att minska kraven ligger i både studenters och lärares intresse.I detta arbete undersöker vi vilka plattformar för samarbete inom matematik dagens studenter på medieteknik-programmet, KTH, använder, samt hur de används och hur de olika plattformarna upplevs påverka studenternas inlärning av matematik. Detta är relevant då matematikkurserna anses vara de svåraste på KTH. För att besvara frågeställningen bads 20 studenter svara på en enkät. Svaren som skickades in var främst i fritext.Resultaten visar att studenter använder sig av Facebook, Skype, Mathoverflow och Reddit vid samarbete i matematik. Dessa plattformar används då studenter finner något svårt i matematiken och behöver diskutera lösningar med andra. Plattformar som Youtube, WolframAlpha och Ludu används enligt studenterna själva för ett samarbete inom matematik. Vi anser dock att de nämnda plattformarna ej faller under vår benämning av plattformsbaserat samarbete. En majoritet av studenterna anser att det finns tillräckligt med resurser på KTH för att hjälpa dem med sin inlärning av matematik. Om KTH skulle införa en plattform för att underlätta matematikinlärningen önskar de flesta att det i sådana fall skulle implementeras ett diskussionsforum där studenter och lärare kan hjälpa varandra med lösningar på matematikproblem.

  • 11949.
    Åberg, Oscar
    et al.
    KTH, Skolan för elektroteknik och datavetenskap (EECS).
    Sparf, Edvin
    KTH, Skolan för elektroteknik och datavetenskap (EECS).
    Validating the Meta Attack Language using MITRE ATT&CK matrix2019Independent thesis Basic level (degree of Bachelor), 10 poäng / 15 hpOppgave
    Abstract [en]

    When more and more devices are getting connected to each other and to the internet, the security of such devices becomes increasingly important. For large organizations with hundreds or even thousands of connected devices, it can be hard to determine the weak spots of the network in terms of security. A way of finding these weak spots is by using threat modelling. One language which can be used for this is the Meta Attack Language(MAL). The purpose of this report is to study which types of cyber attacks can be expressed with MAL. To do so eleven different attack techniques from the cyber attack database MITRE ATT&CK matrix are implemented in MAL. The report shows that many different attacks can be implemented in MAL. Since all of the randomly selected attacks were possible to implement in MAL this suggests that it is possible to implement all of the attacks from the MITRE ATT&CK matrix in MAL.

  • 11950.
    Åborg, Carl
    et al.
    Uppsala Universitet.
    Gulliksen, Jan
    Uppsala Universitet.
    Arbetsmiljö och IT i ett Användarperspektiv2001Inngår i: Användarperspektiv: Människa, Teknik, Organisation / [ed] Bertil Olsson, Stockholm: VINNOVA , 2001, s. 83-90Kapittel i bok, del av antologi (Fagfellevurdert)
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