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Author

Timo Hämäläinen

Other affiliations: Dalian Medical University, Nokia, Dublin Institute of Technology  ...read more
Bio: Timo Hämäläinen is an academic researcher from University of Jyväskylä. The author has contributed to research in topics: Quality of service & Encoder. The author has an hindex of 38, co-authored 560 publications receiving 7648 citations. Previous affiliations of Timo Hämäläinen include Dalian Medical University & Nokia.


Papers
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Proceedings ArticleDOI
23 Mar 2013
TL;DR: A new Real Time Unsupervised Network Intrusion Detection System (RTUNIDS) which monitor network flows in two windows with different sizes and detects network attacks by correlating outliers from multiple clusters is proposed.
Abstract: The most traditional technique for Network Intrusion Detection Systems (NIDSs) is misuse detection which only detects well-known attacks by matching the current behavior of network with pre-defined attacks' signatures. Providing attacks' signatures is costly, time consuming and with the explosive growing number of zero day attacks, using misuse detection mechanism is not an efficient solution. Other techniques which applied on NIDS are supervised and semi-supervised anomaly detection systems which can detect novel attacks by comparing the current behavior of the network to the training sample; however producing labeled or attack-free dataset is difficult for training the engine. Current NIDS solutions monitor bytes, packets' payload or network flows to detect intrusions. Today it is difficult to monitor the payload of packets in high speed network (1-10 Gbps) and recent network attacks are becoming more complex and analyzing only the payload of packets will not produce enough information for detection engine. In this paper we propose a new Real Time Unsupervised Network Intrusion Detection System (RTUNIDS) which monitor network flows in two windows with different sizes and detects network attacks by correlating outliers from multiple clusters. The proposed solution has the ability of detecting different types of intrusions in realtime such as DOS, DDOS, scanning, distribution of worms and any other network attacks which produce huge amount of network traffic and in the meanwhile it detects Bot-Master if the detected attack lunched by Bots.

6 citations

Proceedings ArticleDOI
08 Apr 2002
TL;DR: The functionality and implementation of the wireless Video Control Protocol (VCP) is presented, which has been implemented for developing the functionality for real-time video stream transmission over heterogeneous wireless network technologies.
Abstract: Real-time streaming video is expected to emerge as a key service in different telecommunications systems, including wireless networks. This paper presents the functionality and implementation of the wireless Video Control Protocol (VCP). The protocol has been implemented for developing the functionality for real-time video stream transmission over heterogeneous wireless network technologies. VCP is embedded into a wireless video demonstrator. The demonstrator consists of Windows NT hosts containing a real-time H.263 encoder, video stream parsing functionality, and several network connections, such as wireless LAN, Bluetooth and GSM data. The protocol contains functionality for protecting the video stream transfer and adapting different network technologies together.

6 citations

Proceedings ArticleDOI
25 Apr 2016
TL;DR: It is presented that even though both relay and small cell nodes should be located somewhere at the cell edge, their optimal coordinates are not the same since relays have a limitation that comes from a link between a relay and the master base station.
Abstract: Low power nodes have been a hot topic in research, standardization, and industry communities, which is typically considered under an umbrella term called heterogeneous networking. In this paper, we look at the problem of optimal deployment of low power nodes that could be either small cells connected via the wired backhaul or relays that utilize the same spectrum and the wireless access technology to get connected to the core network. We present that even though both relay and small cell nodes should be located somewhere at the cell edge, their optimal coordinates are not the same since relays have a limitation that comes from a link between a relay and the master base station.

6 citations

Journal ArticleDOI
TL;DR: This case study presents UML-based design and implementation of a wireless video terminal on a multiprocessor system-on-chip (SoC) and proves its suitability and competence in designing complex embedded multimedia terminals.
Abstract: This case study presents UML-based design and implementation of a wireless video terminal on a multiprocessor system-on-chip (SoC). The terminal comprises video encoder and WLAN communications subsystems. In this paper, we present the UML models used in designing the functionality of the subsystems as well as the architecture of the terminal hardware. We use the Koski design flow and tools for fully automated implementation of the terminal on FPGA. Measurements were performed to evaluate the performance of the FPGA implementation. Currently, fully software encoder achieves the frame rate of 3.0 fps with three 50MHz processors, which is one half of a reference C implementation. Thus, using UML and design automation reduces the performance, but we argue that this is highly accepted as we gain significant improvement in design efficiency and flexibility. The experiments with the UML-based design flow proved its suitability and competence in designing complex embedded multimedia terminals.

6 citations

Proceedings ArticleDOI
17 Dec 2010
TL;DR: This paper analyses the effects of Network-on-Chip (NoC) models written in SystemC on simulation speed by evaluating three different mesh sizes using a commercial simulator and OSCI SystemC reference kernel.
Abstract: This paper analyses the effects of Network-on-Chip (NoC) models written in SystemC on simulation speed. Two Register Transfer Level (RTL) models and Approximately Timed (AT) and Loosely Timed (LT) Transaction Level (TL) models are compared against reference RTL VHDL 2D mesh model. Three different mesh sizes are evaluated using a commercial simulator and OSCI SystemC reference kernel. Studied AT model achieved 13–40x speedup with modest 10% estimation error.

5 citations


Cited by
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Journal ArticleDOI

[...]

08 Dec 2001-BMJ
TL;DR: There is, I think, something ethereal about i —the square root of minus one, which seems an odd beast at that time—an intruder hovering on the edge of reality.
Abstract: There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality. Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

33,785 citations

Journal ArticleDOI
TL;DR: Machine learning addresses many of the same research questions as the fields of statistics, data mining, and psychology, but with differences of emphasis.
Abstract: Machine Learning is the study of methods for programming computers to learn. Computers are applied to a wide range of tasks, and for most of these it is relatively easy for programmers to design and implement the necessary software. However, there are many tasks for which this is difficult or impossible. These can be divided into four general categories. First, there are problems for which there exist no human experts. For example, in modern automated manufacturing facilities, there is a need to predict machine failures before they occur by analyzing sensor readings. Because the machines are new, there are no human experts who can be interviewed by a programmer to provide the knowledge necessary to build a computer system. A machine learning system can study recorded data and subsequent machine failures and learn prediction rules. Second, there are problems where human experts exist, but where they are unable to explain their expertise. This is the case in many perceptual tasks, such as speech recognition, hand-writing recognition, and natural language understanding. Virtually all humans exhibit expert-level abilities on these tasks, but none of them can describe the detailed steps that they follow as they perform them. Fortunately, humans can provide machines with examples of the inputs and correct outputs for these tasks, so machine learning algorithms can learn to map the inputs to the outputs. Third, there are problems where phenomena are changing rapidly. In finance, for example, people would like to predict the future behavior of the stock market, of consumer purchases, or of exchange rates. These behaviors change frequently, so that even if a programmer could construct a good predictive computer program, it would need to be rewritten frequently. A learning program can relieve the programmer of this burden by constantly modifying and tuning a set of learned prediction rules. Fourth, there are applications that need to be customized for each computer user separately. Consider, for example, a program to filter unwanted electronic mail messages. Different users will need different filters. It is unreasonable to expect each user to program his or her own rules, and it is infeasible to provide every user with a software engineer to keep the rules up-to-date. A machine learning system can learn which mail messages the user rejects and maintain the filtering rules automatically. Machine learning addresses many of the same research questions as the fields of statistics, data mining, and psychology, but with differences of emphasis. Statistics focuses on understanding the phenomena that have generated the data, often with the goal of testing different hypotheses about those phenomena. Data mining seeks to find patterns in the data that are understandable by people. Psychological studies of human learning aspire to understand the mechanisms underlying the various learning behaviors exhibited by people (concept learning, skill acquisition, strategy change, etc.).

13,246 citations

Journal ArticleDOI
01 Nov 2007
TL;DR: Comprehensive performance comparisons including accuracy, precision, complexity, scalability, robustness, and cost are presented.
Abstract: Wireless indoor positioning systems have become very popular in recent years. These systems have been successfully used in many applications such as asset tracking and inventory management. This paper provides an overview of the existing wireless indoor positioning solutions and attempts to classify different techniques and systems. Three typical location estimation schemes of triangulation, scene analysis, and proximity are analyzed. We also discuss location fingerprinting in detail since it is used in most current system or solutions. We then examine a set of properties by which location systems are evaluated, and apply this evaluation method to survey a number of existing systems. Comprehensive performance comparisons including accuracy, precision, complexity, scalability, robustness, and cost are presented.

4,123 citations

01 Jan 2006

3,012 citations

01 Jan 1990
TL;DR: An overview of the self-organizing map algorithm, on which the papers in this issue are based, is presented in this article, where the authors present an overview of their work.
Abstract: An overview of the self-organizing map algorithm, on which the papers in this issue are based, is presented in this article.

2,933 citations