Control of Robot by Means of Human Thought

Brain computer interface (BCI) is a kind of human machine interface, which provides a new interaction method between human and computer or other equipment. The most significant characteristic of BCI system is that its control input is brain electrical activities acquired from the brain instead of traditional input such as hands or eyes. BCI technique has rapidly developed during last two decades and it has mainly worked as an auxiliary technique to help the disable people improve their life qualities. With the appearance of low cost novel electrical devices such as EMOTIV, BCI technique has been applied to the general public through many useful applications including video gaming, virtual reality and virtual keyboard. The purpose of this research is to be familiar with EMOTIV EPOC system and make use of it to build an EEG based BCI system for controlling an industrial manipulator by means of human thought. To build a BCI system, an acquisition program based on EMOTIV EPOC system is designed and a MFC based dialog that works as an operation panel is presented. Furthermore, the inverse kinematics of RV-3SB industrial robot was solved. In the last part of this research, the designed BCI system with human thought input is examined and the results indicate that the system is running smoothly and displays clearly the motion type and the incremental displacement of the motion.

Using electroencephalography signals to control acoustical processing

Current hearing-assistive technology performs poorly in noisy multi-talker conditions. The goal of this thesis was to establish the feasibility of using EEG to guide acoustic processing in such conditions. To attain this goal, this research developed a model via the constructive research method, relying on literature review. Several approaches have revealed improvements in the performance of hearing-assistive devices under multi-talker conditions, namely beamforming spatial filtering, model-based sparse coding shrinkage, and onset enhancement of the speech signal. Prior research has shown that electroencephalography (EEG) signals contain information that concerns whether the person is actively listening, what the listener is listening to, and where the attended sound source is. This thesis constructed a model for using EEG information to control beamforming, model-based sparse coding shrinkage, and onset enhancement of the speech signal. The purpose of this model is to propose a framework for using EEG signals to control sound processing to select a single talker in a noisy environment containing multiple talkers speaking simultaneously. On a theoretical level, the model showed that EEG can control acoustical processing. An analysis of the model identified a requirement for real-time processing and that the model inherits the computationally intensive properties of acoustical processing, although the model itself is low complexity placing a relatively small load on computational resources. A research priority is to develop a prototype that controls hearing-assistive devices with EEG. This thesis concludes highlighting challenges for future research.

Design of an Embedded Computer Board for Networking Applications

Tämä diplomityö tehtiin Convergens Oy:lle. Convergens on elektroniikan suunnittelutoimisto, joka on erikoistunut sulautettuihin järjestelmiin sekä tietoliikennetekniikkaan. Diplomityön tavoitteena oli suunnitella tietokonekortti tietoliikennesovelluksia varten asiakkaalle, jolta vaatimusmäärittelyt tulivat. Työ on rajattu koskemaan laitteen prototyypin suunnittelua. Työssä suunnitellaan pääasiassa WLAN-tukiaseman tietokone. Tukiasema onasennettavissa toimistoihin, varastoihin, kauppoihin sekä myös liikkuvaan ajoneuvoon. Suunnittelussa on otettu nämä asiat huomioon, ja laitteen akun pystyy lataamaan muun muassa auton akulla. Langattomat tekniikat ovat voimakkaasti yleistymässä, ja tämän työn tukiasema tarjoaakin varteenotettavan vaihtoehdon lukuisilla ominaisuuksillaan. Mukana on mm. GPS, Bluetooth sekä Ethernet-valmius. Langattomien tekniikoiden lisäksi myös sulautetut järjestelmät ovat voimakkaasti yleistymässä, ja nykyään mikroprosessoreita löytääkin lähesmistä vain. Tässä projektissa käytetty prosessori on nopeutensa puolesta kilpailukykyinen, ja siitä löytyy useita eri rajapintoja. Jatkossa tietokonekortille on myös tulossa WiMAX-tuki, joka lisää tukiaseman tulevaisuuden arvoa asiakkaalle. Projektiin valittu Freescalen MPC8321E-prosessori on PowerPC-arkkitehtuuriin perustuva ja juuri markkinoille ilmestynyt. Tämä toi mukanaan lisähaasteen, sillä kyseisestä prosessorista ei ollut vielä kaikkea tietoa saatavilla. Mekaniikka toi omat haasteensa mukanaan, sillä se rajoitti piirilevyn koonniin, että ylimääräistä piirilevytilaa ei juurikaan jäänyt. Tämän takia esimerkiksi DDR-muistit olivat haastavia reitittää, sillä muistivetojen on oltava melko samanpituisia keskenään. Käyttöjärjestelmänä projektissa käytetään Linuxia. Suunnittelu alkoi keväällä 2007 ja toimiva prototyyppi oli valmis alkusyksystä. Prototyypin testaus osoitti, että tietokonekortti kykenee täyttämään kaikki asiakkaan vaatimukset. Prototyypin testauksessa löytyneet viat ja optimoinnit on tarkoitus korjata tuotantomalliin, joten se antaa hyvän pohjan jatkosuunnittelua varten.

Search Interfaces on the Web: Querying and Characterizing

Current-day web search engines (e.g., Google) do not crawl and index a significant portion of theWeb and, hence, web users relying on search engines only are unable to discover and access a large amount of information from the non-indexable part of the Web. Specifically, dynamic pages generated based on parameters provided by a user via web search forms (or search interfaces) are not indexed by search engines and cannot be found in searchers’ results. Such search interfaces provide web users with an online access to myriads of databases on the Web. In order to obtain some information from a web database of interest, a user issues his/her query by specifying query terms in a search form and receives the query results, a set of dynamic pages that embed required information from a database. At the same time, issuing a query via an arbitrary search interface is an extremely complex task for any kind of automatic agents including web crawlers, which, at least up to the present day, do not even attempt to pass through web forms on a large scale. In this thesis, our primary and key object of study is a huge portion of the Web (hereafter referred as the deep Web) hidden behind web search interfaces. We concentrate on three classes of problems around the deep Web: characterization of deep Web, finding and classifying deep web resources, and querying web databases. Characterizing deep Web: Though the term deep Web was coined in 2000, which is sufficiently long ago for any web-related concept/technology, we still do not know many important characteristics of the deep Web. Another matter of concern is that surveys of the deep Web existing so far are predominantly based on study of deep web sites in English. One can then expect that findings from these surveys may be biased, especially owing to a steady increase in non-English web content. In this way, surveying of national segments of the deep Web is of interest not only to national communities but to the whole web community as well. In this thesis, we propose two new methods for estimating the main parameters of deep Web. We use the suggested methods to estimate the scale of one specific national segment of the Web and report our findings. We also build and make publicly available a dataset describing more than 200 web databases from the national segment of the Web. Finding deep web resources: The deep Web has been growing at a very fast pace. It has been estimated that there are hundred thousands of deep web sites. Due to the huge volume of information in the deep Web, there has been a significant interest to approaches that allow users and computer applications to leverage this information. Most approaches assumed that search interfaces to web databases of interest are already discovered and known to query systems. However, such assumptions do not hold true mostly because of the large scale of the deep Web – indeed, for any given domain of interest there are too many web databases with relevant content. Thus, the ability to locate search interfaces to web databases becomes a key requirement for any application accessing the deep Web. In this thesis, we describe the architecture of the I-Crawler, a system for finding and classifying search interfaces. Specifically, the I-Crawler is intentionally designed to be used in deepWeb characterization studies and for constructing directories of deep web resources. Unlike almost all other approaches to the deep Web existing so far, the I-Crawler is able to recognize and analyze JavaScript-rich and non-HTML searchable forms. Querying web databases: Retrieving information by filling out web search forms is a typical task for a web user. This is all the more so as interfaces of conventional search engines are also web forms. At present, a user needs to manually provide input values to search interfaces and then extract required data from the pages with results. The manual filling out forms is not feasible and cumbersome in cases of complex queries but such kind of queries are essential for many web searches especially in the area of e-commerce. In this way, the automation of querying and retrieving data behind search interfaces is desirable and essential for such tasks as building domain-independent deep web crawlers and automated web agents, searching for domain-specific information (vertical search engines), and for extraction and integration of information from various deep web resources. We present a data model for representing search interfaces and discuss techniques for extracting field labels, client-side scripts and structured data from HTML pages. We also describe a representation of result pages and discuss how to extract and store results of form queries. Besides, we present a user-friendly and expressive form query language that allows one to retrieve information behind search interfaces and extract useful data from the result pages based on specified conditions. We implement a prototype system for querying web databases and describe its architecture and components design.