Flash Memory Cells Reliability Parameters Investigation

The present work is a part of the large project with purpose to qualify the Flash memory for automotive application using a standardized test and measurement flow. High memory reliability and data retention are the most critical parameters in this application. The current work covers the functional tests and data retention test. The purpose of the data retention test is to obtain the data retention parameters of the designed memory, i.e. the maximum time of information storage at specified conditions without critical charge leakage. For this purpose the charge leakage from the cells, which results in decrease of cells threshold voltage, was measured after a long-time hightemperature treatment at several temperatures. The amount of lost charge for each temperature was used to calculate the Arrhenius constant and activation energy for the discharge process. With this data, the discharge of the cells at different temperatures during long time can be predicted and the probability of data loss after years can be calculated. The memory chips, investigated in this work, were 0.035 μm CMOS Flash memory testchips, designed for further use in the Systems-on-Chips for automotive electronics.

Unsupervised visual object categorization

The number of digital images has been increasing exponentially in the last few years. People have problems managing their image collections and finding a specific image. An automatic image categorization system could help them to manage images and find specific images. In this thesis, an unsupervised visual object categorization system was implemented to categorize a set of unknown images. The system is unsupervised, and hence, it does not need known images to train the system which needs to be manually obtained. Therefore, the number of possible categories and images can be huge. The system implemented in the thesis extracts local features from the images. These local features are used to build a codebook. The local features and the codebook are then used to generate a feature vector for an image. Images are categorized based on the feature vectors. The system is able to categorize any given set of images based on the visual appearance of the images. Images that have similar image regions are grouped together in the same category. Thus, for example, images which contain cars are assigned to the same cluster. The unsupervised visual object categorization system can be used in many situations, e.g., in an Internet search engine. The system can categorize images for a user, and the user can then easily find a specific type of image.

On the development of object functions and restrictions for shapes made with a turret punch press

This study presents the information required to describe the machine and device resources in the turret punch press environment which are needed for the development of the analysing method for automated production. The description of product and device resources and their interconnectedness is the starting point for method comparison the development of expenses, production planning and the performance of optimisation. The manufacturing method cannot be optimized unless the variables and their interdependence are known. Sheet metal parts in particular may then become remarkably complex, and their automatic manufacture may be difficult or, with some automatic equipment, even impossible if not know manufacturing properties. This thesis consists of three main elements, which constitute the triangulation. In the first phase of triangulation, the manufacture occuring on a turret punch press is examined in order to find the factors that affect the efficiency of production. In the second phase of triangulation, the manufacturability of products on turret punch presses is examined through a set of laboratory tests. The third phase oftriangulation involves an examination of five industry parts. The main key findings of this study are: all possible efficiency in high automation level machining cannot be achieved unless the raw materials used in production and the dependencies of the machine and tools are well known. Machine-specific manufacturability factors for turret punch presses were not taken into account in the industrial case samples. On the grounds of the performed tests and industrial case samples, the designer of a sheet metal product can directly influence the machining time, material loss, energy consumption and the number of tools required on a turret punch press by making decisions in the way presented in the hypothesis of thisstudy. The sheet metal parts to be produced can be optimised to bemanufactured on a turret punch press when the material to be used and the kinds of machine and tool options available are known. This provides in-depth knowledge of the machine and tool properties machine and tool-specifically. None of the optimisation starting points described here is a separate entity; instead, they are all connected to each other.

Comparison of Local Feature Detectors and Descriptors for Visual Object Categorization

Local features are used in many computer vision tasks including visual object categorization, content-based image retrieval and object recognition to mention a few. Local features are points, blobs or regions in images that are extracted using a local feature detector. To make use of extracted local features the localized interest points are described using a local feature descriptor. A descriptor histogram vector is a compact representation of an image and can be used for searching and matching images in databases. In this thesis the performance of local feature detectors and descriptors is evaluated for object class detection task. Features are extracted from image samples belonging to several object classes. Matching features are then searched using random image pairs of a same class. The goal of this thesis is to find out what are the best detector and descriptor methods for such task in terms of detector repeatability and descriptor matching rate.

Verbal learning in mild cognitive impairment and alzheimer's disease : behavioural and neural approaches

The main focus of the present thesis was at verbal episodic memory processes that are particularly vulnerable to preclinical and clinical Alzheimer’s disease (AD). Here these processes were studied by a word learning paradigm, cutting across the domains of memory and language learning studies. Moreover, the differentiation between normal aging, mild cognitive impairment (MCI) and AD was studied by the cognitive screening test CERAD. In study I, the aim was to examine how patients with amnestic MCI differ from healthy controls in the different CERAD subtests. Also, the sensitivity and specificity of the CERAD screening test to MCI and AD was examined, as previous studies on the sensitivity and specificity of the CERAD have not included MCI patients. The results indicated that MCI is characterized by an encoding deficit, as shown by the overall worse performance on the CERAD Wordlist learning test compared with controls. As a screening test, CERAD was not very sensitive to MCI. In study II, verbal learning and forgetting in amnestic MCI, AD and healthy elderly controls was investigated with an experimental word learning paradigm, where names of 40 unfamiliar objects (mainly archaic tools) were trained with or without semantic support. The object names were trained during a 4-day long period and a follow-up was conducted one week, 4 weeks and 8 weeks after the training period. Manipulation of semantic support was included in the paradigm because it was hypothesized that semantic support might have some beneficial effects in the present learning task especially for the MCI group, as semantic memory is quite well preserved in MCI in contrast to episodic memory. We found that word learning was significantly impaired in MCI and AD patients, whereas forgetting patterns were similar across groups. Semantic support showed a beneficial effect on object name retrieval in the MCI group 8 weeks after training, indicating that the MCI patients’ preserved semantic memory abilities compensated for their impaired episodic memory. The MCI group performed equally well as the controls in the tasks tapping incidental learning and recognition memory, whereas the AD group showed impairment. Both the MCI and the AD group benefited less from phonological cueing than the controls. Our findings indicate that acquisition is compromised in both MCI and AD, whereas long13 term retention is not affected to the same extent. Incidental learning and recognition memory seem to be well preserved in MCI. In studies III and IV, the neural correlates of naming newly learned objects were examined in healthy elderly subjects and in amnestic MCI patients by means of positron emission tomography (PET) right after the training period. The naming of newly learned objects by healthy elderly subjects recruited a left-lateralized network, including frontotemporal regions and the cerebellum, which was more extensive than the one related to the naming of familiar objects (study III). Semantic support showed no effects on the PET results for the healthy subjects. The observed activation increases may reflect lexicalsemantic and lexical-phonological retrieval, as well as more general associative memory mechanisms. In study IV, compared to the controls, the MCI patients showed increased anterior cingulate activation when naming newly learned objects that had been learned without semantic support. This suggests a recruitment of additional executive and attentional resources in the MCI group.

Neural correlates of language learning in adults

The human language-learning ability persists throughout life, indicating considerable flexibility at the cognitive and neural level. This ability spans from expanding the vocabulary in the mother tongue to acquisition of a new language with its lexicon and grammar. The present thesis consists of five studies that tap both of these aspects of adult language learning by using magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI) during language processing and language learning tasks. The thesis shows that learning novel phonological word forms, either in the native tongue or when exposed to a foreign phonology, activates the brain in similar ways. The results also show that novel native words readily become integrated in the mental lexicon. Several studies in the thesis highlight the left temporal cortex as an important brain region in learning and accessing phonological forms. Incidental learning of foreign phonological word forms was reflected in functionally distinct temporal lobe areas that, respectively, reflected short-term memory processes and more stable learning that persisted to the next day. In a study where explicitly trained items were tracked for ten months, it was found that enhanced naming-related temporal and frontal activation one week after learning was predictive of good long-term memory. The results suggest that memory maintenance is an active process that depends on mechanisms of reconsolidation, and that these process vary considerably between individuals. The thesis put special emphasis on studying language learning in the context of language production. The neural foundation of language production has been studied considerably less than that of perceptive language, especially on the sentence level. A well-known paradigm in language production studies is picture naming, also used as a clinical tool in neuropsychology. This thesis shows that accessing the meaning and phonological form of a depicted object are subserved by different neural implementations. Moreover, a comparison between action and object naming from identical images indicated that the grammatical class of the retrieved word (verb, noun) is less important than the visual content of the image. In the present thesis, the picture naming was further modified into a novel paradigm in order to probe sentence-level speech production in a newly learned miniature language. Neural activity related to grammatical processing did not differ between the novel language and the mother tongue, but stronger neural activation for the novel language was observed during the planning of the upcoming output, likely related to more demanding lexical retrieval and short-term memory. In sum, the thesis aimed at examining language learning by combining different linguistic domains, such as phonology, semantics, and grammar, in a dynamic description of language processing in the human brain.

Bag-of-Features Approach to Unsupervised Visual Object Categorisation

The large and growing number of digital images is making manual image search laborious. Only a fraction of the images contain metadata that can be used to search for a particular type of image. Thus, the main research question of this thesis is whether it is possible to learn visual object categories directly from images. Computers process images as long lists of pixels that do not have a clear connection to high-level semantics which could be used in the image search. There are various methods introduced in the literature to extract low-level image features and also approaches to connect these low-level features with high-level semantics. One of these approaches is called Bag-of-Features which is studied in the thesis. In the Bag-of-Features approach, the images are described using a visual codebook. The codebook is built from the descriptions of the image patches using clustering. The images are described by matching descriptions of image patches with the visual codebook and computing the number of matches for each code. In this thesis, unsupervised visual object categorisation using the Bag-of-Features approach is studied. The goal is to find groups of similar images, e.g., images that contain an object from the same category. The standard Bag-of-Features approach is improved by using spatial information and visual saliency. It was found that the performance of the visual object categorisation can be improved by using spatial information of local features to verify the matches. However, this process is computationally heavy, and thus, the number of images must be limited in the spatial matching, for example, by using the Bag-of-Features method as in this study. Different approaches for saliency detection are studied and a new method based on the Hessian-Affine local feature detector is proposed. The new method achieves comparable results with current state-of-the-art. The visual object categorisation performance was improved by using foreground segmentation based on saliency information, especially when the background could be considered as clutter.

Building object-oriented software with the D-Bus messaging system

Object-oriented programming is a widely adopted paradigm for desktop software development. This paradigm partitions software into separate entities, objects, which consist of data and related procedures used to modify and inspect it. The paradigm has evolved during the last few decades to emphasize decoupling between object implementations, via means such as explicit interface inheritance and event-based implicit invocation. Inter-process communication (IPC) technologies allow applications to interact with each other. This enables making software distributed across multiple processes, resulting in a modular architecture with benefits in resource sharing, robustness, code reuse and security. The support for object-oriented programming concepts varies between IPC systems. This thesis is focused on the D-Bus system, which has recently gained a lot of users, but is still scantily researched. D-Bus has support for asynchronous remote procedure calls with return values and a content-based publish/subscribe event delivery mechanism. In this thesis, several patterns for method invocation in D-Bus and similar systems are compared. The patterns that simulate synchronous local calls are shown to be dangerous. Later, we present a state-caching proxy construct, which avoids the complexity of properly asynchronous calls for object inspection. The proxy and certain supplementary constructs are presented conceptually as generic object-oriented design patterns. The e ect of these patterns on non-functional qualities of software, such as complexity, performance and power consumption, is reasoned about based on the properties of the D-Bus system. The use of the patterns reduces complexity, but maintains the other qualities at a good level. Finally, we present currently existing means of specifying D-Bus object interfaces for the purposes of code and documentation generation. The interface description language used by the Telepathy modular IM/VoIP framework is found to be an useful extension of the basic D-Bus introspection format.

Memory studies - kohti tutkimusalueen vakiintumista

Teemanumero 2/2011: Media ja menneisyys.

Lectio praecursoria : Systems between information and knowledge : in a memory management model of an extended enterprise

VTT Jouni Meriluodon valtio-opin alaan kuuluva väitöskirja Systems between information and knowledge : in a memory management model of an extended enterprise tarkastettiin 21.6.2011 Helsingin yliopistossa.

Memory Effects in the Dynamics of Open Quantum Systems

In this Thesis various aspects of memory effects in the dynamics of open quantum systems are studied. We develop a general theoretical framework for open quantum systems beyond the Markov approximation which allows us to investigate different sources of memory effects and to develop methods for harnessing them in order to realise controllable open quantum systems. In the first part of the Thesis a characterisation of non-Markovian dynamics in terms of information flow is developed and applied to study different sources of memory effects. Namely, we study nonlocal memory effects which arise due to initial correlations between two local environments and further the memory effects induced by initial correlations between the open system and the environment. The last part focuses on describing two all-optical experiment in which through selective preparation of the initial environment states the information flow between the system and the environment can be controlled. In the first experiment the system is driven from the Markovian to the non- Markovian regime and the degree of non-Markovianity is determined. In the second experiment we observe the nonlocal nature of the memory effects and provide a novel method to experimentally quantify frequency correlations in photonic environments via polarisation measurements.

Neurocognitive changes in early-stage Parkinson's disease : functional and structural brain correlates of memory and verbal functions

Resultaten påvisade små, men mätbara försämringar i minnes- och verbal förmåga hos personer som haft Parkinsons sjukdom under tre år. Jämfört med en kontrollgrupp uppvisade Parkinsonpatienter avvikande responser i hjärnans elektriska aktivitet under en korttidsminnesuppgift, och de presterade även sämre i olika typer av andra minnesuppgifter. Försämring i en specifik typ av minnesuppgift korrelerade med förminskad volym i höger hjärnhalva. Samband hittades också mellan sämre verbal förmåga och förminskad volym i djupa hjärnstrukturer. Förminskad hjärnvolym har tidigare påvisats hos dementa patienter i senare sjukdomsstadier. Forskningsresultaten bidrar med ny kunskap om kognitiva symptom och deras neurala bakgrund vid Parkinsons sjukdom. De tyder också på att tidig kognitiv funktionsnedsättning kan identifieras, vilket kan bidra till utvecklingen av sjukdomens behandling. Parkinsons sjukdom är den näst vanligaste neurogeriatriska sjukdomen efter Alzheimers sjukdom. Symptomen uppstår som följd av förminskad produktion av hjärnans transmittorämne dopamin. Parkinsons sjukdom har traditionellt betraktats som en progressiv motorisk sjukdom. Ny forskning tyder på att multipla hjärnsystem skadas, vilket resulterar i att även tankeprocesser påverkas. 75-80% uppskattas insjukna i demens 10-15 år efter diagnos, men det kognitiva sjukdomsförloppet och orsaken till demenssymptomen är tillsvidare okänd. I Finland uppskattas ca 10-12 000 personer ha Parkinsons sjukdom, varav ca 3 000 uppskattas ha demens. ----------------------------------------------------------------------------------------------------------------------------------------------------- Tutkimuksessa todettiin lieviä muutoksia muisti- ja kielellisissä toiminnoissa alle kolme vuotta sairastaneilla Parkinson-potilailla. Potilailla havaittiin poikkeavia aivosähkötoiminnan vasteita lyhytkestoista muistia mittaavan tehtävän aikana. Potilaat suoriutuivat myös verrokkiryhmää heikommin useissa muistitehtävissä. Heikentynyt tahaton muisti liittyi pienempään aivokuoren harmaan aineen paikalliseen tilavuuteen. Heikompi kielellinen suoriutuminen liittyi pienempään harmaan aineen tilavuuteen aivojen syvissä rakenteissa. Pienentyneitä aivorakenteiden tilavuuksia on aiemmin todettu dementoituneilla Parkinson-potilailla sairauden myöhemmissä vaiheissa. Tutkimustulokset tuovat uutta tietoa Parkinsonin taudin kognitiivisista oireista ja niiden aivoperäisestä taustasta. Tulosten perusteella on mahdollista tunnistaa jo varhaisia kognitiivisia muutoksia, mikä voi mahdollistaa tehokkaamman hoidon kohdentamisen. Parkinsonin tauti on Alzheimerin taudin jälkeen toiseksi yleisin neurogeriatrinen sairaus. Oirekuva liittyy aivojen dopaminergisen järjestelmän rappeutumiseen. Perinteisesti liikehäiriösairaudeksi luokiteltu sairaus vaurioittaa lukuisia muita aivojärjestelmiä aiheuttaen muutoksia myös mm. ajattelutoiminnoissa. Pitkään sairastaneista 75–80 prosentilla esiintyy dementiaoireita, mutta oireiden syy ja kehityskaari tunnetaan toistaiseksi huonosti. Suomessa on arviolta 10–12 000 Parkinson-potilasta, joista noin 3 000 arvioidaan kärsivän dementiaoireista.

Local Features in Image and Video Processing - Object Class Matching and Video Shot Detection

The usage of digital content, such as video clips and images, has increased dramatically during the last decade. Local image features have been applied increasingly in various image and video retrieval applications. This thesis evaluates local features and applies them to image and video processing tasks. The results of the study show that 1) the performance of different local feature detector and descriptor methods vary significantly in object class matching, 2) local features can be applied in image alignment with superior results against the state-of-the-art, 3) the local feature based shot boundary detection method produces promising results, and 4) the local feature based hierarchical video summarization method shows promising new new research direction. In conclusion, this thesis presents the local features as a powerful tool in many applications and the imminent future work should concentrate on improving the quality of the local features.