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KTH Royal Institute of Technology, Sweden

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19 Papers

A Formal Approach to Anomaly Detection

Topic: Model Selection

Authors: André Eriksson and Hedvig Kjellström

Affiliation: KTH Royal Institute of Technology, Sweden

Digital Object Identifier: 10.5220/0005710803170326

Proceedings of ICPRAM 2016, ISBN: 978-989-758-173-1

Quick Abstract

While many advances towards effective anomaly detection techniques targeting specific applications have been made in recent years, little work has been done to develop application-agnostic approaches to the subject. In this article, we present such an approach, in which anomaly detection methods are treated as formal, structured objects. We consider a general class of methods, with an emphasis on methods that utilize structural properties of the data they operate on. For this class of methods, we develop a decomposition into sub-methods—simple, restricted objects, which may be reasoned about independently and combined to form methods. As we show, this formalism enables the construction of software that facilitates formulating, implementing, evaluating, as well as algorithmically finding and calibrating anomaly detection methods.

Related Ontology Subjects/Areas/Topics (3)

Model Selection

Pattern Recognition

Theory and Methods

A 180 nm-CMOS Asymmetric UWB-RFID Tag with Real-time Remote-monitored ECG-sensing

Topics: Microelectronics; Health Monitoring Devices; Low-Power Design; Wireless Systems; Electrocardiography and Heart Monitoring

Authors: Jue Shen ¹ , Jia Mao ¹ , Geng Yang ¹ , Li Xie ¹ , Yi Feng ¹ , Majid Nejad ² , Zhuo Zou ¹ , Hannu Tenhunen ¹ and Li-Rong Zheng ³

Affiliations: ¹ KTH-Royal Institute of Technology, Sweden , ² Hakim Sabzevari University, Iran, Islamic Republic of , ³ KTH-Royal Institute of Technology and Fudan University, Sweden

Digital Object Identifier: 10.5220/0005286302100215

Proceedings of BIODEVICES 2015/BIOSTEC, ISBN: 978-989-758-071-0

Quick Abstract

This paper proposes an asymmetric ultra-wideband - radio frequency identification (UWB-RFID) tag with electrocardiogram (ECG)-sensing capability for patients remote-monitoring in hospital environment. A UWB-RFID communication protocol is suggested for real-time transmission of undistorted ECG by interleaving ADC sampling and burst-mode UWB transmission. The proposed system shows a maximum accessing capability of 400 tags/second at 1.5 KHz ECG sampling rate with 10 Mbps UWB pulse rate. The tag consists of UHF-RFID receiver, UWB transmitter, ECG analog front-end, multi-input ADC and baseband circuitry integrated on two silicon dies. It was implemented by 6 mm2 -sized 180 nm CMOS technology. Electrodes for ECG-sensing are manufactured by inkjet-printing on polyimide substrate. Experiment results show that the tag transmits UWB pulses at 1 Mbps rate with 18 µW power. The printed electrodes conduct ECG waveform comparable to commercial electrodes.

Related Ontology Subjects/Areas/Topics (10)

Biomedical Engineering	Health Monitoring Devices	Microelectronics
Biomedical Instruments and Devices	Human-Computer Interaction	Physiological Computing Systems
Devices	Low-Power Design	Wireless Systems
Electrocardiography and Heart Monitoring

A Smart Catheter System for Minimally Invasive Brain Monitoring

Topics: Biomedical Instrumentation; Biomedical Sensors; Health Monitoring Devices

Authors: Dongxuan Bao ¹ , Zhuo Zou ² , Yuxiang Huan ¹ , Chuanying Zhai ² , Tiberiu Bagaian ³ , Hannu Tenhunen ² , Bengt Källbäck ³ and Li-Rong Zheng ⁴

Affiliations: ¹ Fudan University, China , ² KTH-Royal Institute of Technology, Sweden , ³ CathPrint AB, Sweden , ⁴ Fudan University and KTH-Royal Institute of Technology, China

Digital Object Identifier: 10.5220/0005285501980203

Proceedings of BIODEVICES 2015/BIOSTEC, ISBN: 978-989-758-071-0

Quick Abstract

This paper demonstrates a smart catheter system with intracranial pressure (ICP) and temperature sensing capability which is designed for real-time monitoring in traumatic brain injury (TBI) therapy. It uses a single flexible catheter with a 1 mm (3 Fr) diameter that integrates electrodes and sophisticated silicon chip on flexible substrates, enabling multimodality monitoring of physiological signals. A micro-electro-mechanical-system (MEMS) catheter pressure sensor is mounted on the distal end. It can be used for detecting both pressure and temperature by different switch configurations, which minimizes the size of catheter and reduces the cost. The interconnects (signalling conductors) are printed on a bio-compatible flexible substrate, and the sensor is interfaced with an embedded electronic system at the far-end. The electronic system consists of analog front end with analog-to-digital converter (ADC), a microcontroller, and data interface to the hospital infrastructure with a graphical user interface (GUI). The overall smart catheter system achieves a pressure sensing root mean square error (RMSE) of +-1.5 mmHg measured from 20 mmHg to 300 mmHg above 1 atm and a temperature sensing RMSE of +-0.08 ºC measured from 32 ºC to 42 ºC. The sampling rate can be up to 10S/s. The in vivo performance is demonstrated in laboratory animals.

Related Ontology Subjects/Areas/Topics (8)

Biomedical Engineering	Biomedical Sensors	Human-Computer Interaction
Biomedical Instrumentation	Devices	Physiological Computing Systems
Biomedical Instruments and Devices	Health Monitoring Devices

Gradual Improvement of Image Descriptor Quality

Topics: Classification; Object Recognition

Authors: Heydar Maboudi Afkham , Carl Henrik Ek and Stefan Carlsson

Affiliation: KTH, Sweden

Digital Object Identifier: 10.5220/0004826402330238

Proceedings of ICPRAM 2014, ISBN: 978-989-758-018-5

Quick Abstract

In this paper, we propose a framework for gradually improving the quality of an already existing image descriptor. The descriptor used in this paper (Afkham et al., 2013) uses the response of a series of discriminative components for summarizing each image. As we will show, this descriptor has an ideal form in which all categories become linearly separable. While, reaching this form is not feasible, we will argue how by replacing a small fraction of these components, it is possible to obtain a descriptor which is, on average, closer to this ideal form. To do so, we initially identify which components do not contribute to the quality of the descriptor and replace them with more robust components. Here, a joint feature selection method is used to find improved components. As our experiments show, this change directly reflects in the capability of the resulting descriptor in discriminating between different categories.

Related Ontology Subjects/Areas/Topics (6)

Applications		Object Recognition		Software Engineering
Classification		Pattern Recognition		Theory and Methods

Initialization Framework for Latent Variable Models

Topics: Classification; Clustering; Object Recognition

Authors: Heydar Maboudi Afkham , Carl Henrik Ek and Stefan Carlsson

Affiliation: KTH, Sweden

Digital Object Identifier: 10.5220/0004826302270232

Proceedings of ICPRAM 2014, ISBN: 978-989-758-018-5

Quick Abstract

In this paper, we discuss the properties of a class of latent variable models that assumes each labeled sample is associated with set of different features, with no prior knowledge of which feature is the most relevant feature to be used. Deformable-Part Models (DPM) can be seen as good example of such models. While Latent SVM framework (LSVM) has proven to be an efficient tool for solving these models, we will argue that the solution found by this tool is very sensitive to the initialization. To decrease this dependency, we propose a novel clustering procedure, for these problems, to find cluster centers that are shared by several sample sets while ignoring the rest of the cluster centers. As we will show, these cluster centers will provide a robust initialization for the LSVM framework.

Related Ontology Subjects/Areas/Topics (7)

Applications	Object Recognition	Software Engineering
Classification	Pattern Recognition	Theory and Methods
Clustering

Ontology Integration with Contextual Information

Topics: Knowledge Representation and Reasoning; Model-Based Reasoning; Ontologies; Knowledge-Based Systems

Author: Dan Wu

Affiliation: School of Information and Communication Technology, Sweden

Digital Object Identifier: 10.5220/0004820504850490

Proceedings of ICAART 2014, ISBN: 978-989-758-015-4

Quick Abstract

By studying ontologies in an ontology repository, context rules are developed to improve ontology integration result. A context rule contains conditions for identifying a context. These context conditions are described by, so called, context criteria, which are, e.g., author and domain of an ontology. When the conditions, in a rule, are met, the rule is fired and the contextual information, in the body of the rule, is inserted into the reasoner, which is used for ontology integration. An example shows the construction of a context rule. The rule is used for an ontology integration. The integration result is indeed improved comparing with integration without contextual information.

Related Ontology Subjects/Areas/Topics (12)

Artificial Intelligence	Enterprise Ontologies	Model-Based Reasoning
e-Business	Formal Methods	Ontologies
Enterprise Engineering	Knowledge Representation and Reasoning	Simulation and Modeling
Enterprise Information Systems	Knowledge-Based Systems	Symbolic Systems

Trawl-door Shape Optimization with 3D CFD Models and Local Surrogates

Authors: Elvar Hermannsson ¹ , Leifur Leifsson ² , Slawomir Koziel ² , Piotr Kurgan ² and Adrian Bekasiewicz ³

Affiliations: ¹ KTH Royal Institute of Technology, Sweden , ² Reykjavik University, Iceland , ³ Gdansk University of Technology, Poland

Digital Object Identifier: 10.5220/0005131307750784

Proceedings of SDDOM 2014/SIMULTECH, ISBN: 978-989-758-038-3

Quick Abstract

Design and optimization of trawl-doors are key factors in minimizing the fuel consumption of fishing vessels. This paper discusses optimization of the trawl-door shapes using high-fidelity 3D computational fluid dynamic (CFD) models. The accurate 3D CFD models are computationally expensive and, therefore, the direct use of traditional optimization algorithms, which often require a large number of evaluations, may be prohibitive. The design approach presented here is a variation of sequential approximate optimization exploiting low-order local response surface models of the expensive 3D CFD simulations. The algorithm is applied to the design of modern and airfoil-shaped trawl-doors.

Hierarchical Supporting Structure for Dynamic Organization in Many-core Computing Systems

Authors: Liang Guang ¹ , Syed M. A. H. Jafri ² , Bo Yang ¹ , Juha Plosila ¹ and Hannu Tenhunen ²

Affiliations: ¹ University of Turku, Finland , ² University of Turku and Royal Institute of Technology, Finland

Digital Object Identifier: 10.5220/0004389702520261

Proceedings of SANES 2013/PECCS, ISBN: 978-989-8565-43-3

Quick Abstract

Hierarchical supporting structures for dynamic organization in many-core computing systems are presented. With profound hardware variations and unpredictable errors, dependability becomes a challenging issue in the emerging many-core systems. To provide fault-tolerance against processor failures or performance degradation, dynamic organization is proposed which allows clusters to be created and updated at the run-time. Hierarchical supporting structures are designed for each level of monitoring agents, to enable the tracing, storing and updating of component and system status. These supporting structures need to follow software/hardware co-design to provide small and scalable overhead, while accommodating the functions of agents on the corresponding level. This paper presents the architectural design, functional simulation and implementation analysis. The study demonstrates that the proposed structures facilitate the dynamic organization in case of processor failures and incur small area overhead on many-core systems.

Qualitative Vocabulary based Descriptor

Topics: Classification; Image Understanding

Authors: Heydar Maboudi Afkham , Carl Henrik Ek and Stefan Carlsson

Affiliation: KTH, Sweden

Digital Object Identifier: 10.5220/0004266901880193

Proceedings of ICPRAM 2013, ISBN: 978-989-8565-41-9

Quick Abstract

Creating a single feature descriptors from a collection of feature responses is an often occurring task. As such the bag-of-words descriptors have been very successful and applied to data from a large range of different domains. Central to this approach is making an association of features to words. In this paper we present a new and novel approach to feature to word association problem. The proposed method creates a more robust representation when data is noisy and requires less words compared to the traditional methods while retaining similar performance. We experimentally evaluate the method on a challenging image classification data-set and show significant improvement to the state of the art.

Related Ontology Subjects/Areas/Topics (6)

Applications		Computer Vision, Visualization and Computer Graphics		Pattern Recognition
Classification		Image Understanding		Theory and Methods

The Path Kernel

Topic: Kernel Methods

Authors: Andrea Baisero , Florian T. Pokorny , Danica Kragic and Carl Henrik Ek

Affiliation: KTH Royal Institute of Technology, Sweden

Digital Object Identifier: 10.5220/0004267300500057

Proceedings of ICPRAM 2013, ISBN: 978-989-8565-41-9

Quick Abstract

Kernel methods have been used very successfully to classify data in various application domains. Traditionally, kernels have been constructed mainly for vectorial data defined on a specific vector space. Much less work has been addressing the development of kernel functions for non-vectorial data. In this paper, we present a new kernel for encoding sequential data. We present our results comparing the proposed kernel to the state of the art, showing a significant improvement in classification and a much improved robustness and interpretability.

Related Ontology Subjects/Areas/Topics (3)

Kernel Methods

Pattern Recognition

Theory and Methods