Local Binary Patterns in Focal-Plane Processing. Analysis and Applications

Feature extraction is the part of pattern recognition, where the sensor data is transformed into a more suitable form for the machine to interpret. The purpose of this step is also to reduce the amount of information passed to the next stages of the system, and to preserve the essential information in the view of discriminating the data into different classes. For instance, in the case of image analysis the actual image intensities are vulnerable to various environmental effects, such as lighting changes and the feature extraction can be used as means for detecting features, which are invariant to certain types of illumination changes. Finally, classification tries to make decisions based on the previously transformed data. The main focus of this thesis is on developing new methods for the embedded feature extraction based on local non-parametric image descriptors. Also, feature analysis is carried out for the selected image features. Low-level Local Binary Pattern (LBP) based features are in a main role in the analysis. In the embedded domain, the pattern recognition system must usually meet strict performance constraints, such as high speed, compact size and low power consumption. The characteristics of the final system can be seen as a trade-off between these metrics, which is largely affected by the decisions made during the implementation phase. The implementation alternatives of the LBP based feature extraction are explored in the embedded domain in the context of focal-plane vision processors. In particular, the thesis demonstrates the LBP extraction with MIPA4k massively parallel focal-plane processor IC. Also higher level processing is incorporated to this framework, by means of a framework for implementing a single chip face recognition system. Furthermore, a new method for determining optical flow based on LBPs, designed in particular to the embedded domain is presented. Inspired by some of the principles observed through the feature analysis of the Local Binary Patterns, an extension to the well known non-parametric rank transform is proposed, and its performance is evaluated in face recognition experiments with a standard dataset. Finally, an a priori model where the LBPs are seen as combinations of n-tuples is also presented

Expectations of elderly people on the nurse-client relationship and interaction in home care : "When I see the nurse's smiling face it feels likes sunshine on a rainy and gloomy day"

The purpose of the thesis was to explore expectations of elderly people on the nurse-client relationship and interaction in home care. The aim is to improve the quality of care to better meet the needs of the clients. A qualitative approach was adopted. Semi-structured theme interviews were used for data collection. The interviews were conducted during spring 2006. Six elderly clients of a private home care company in Southern Finland acted as informants. Content analysis was used as the method of data analysis. The findings suggest that clients expect nurses to provide professional care with loving-kindness. Trust and mutual, active interaction were expected from the nurse-client relationship. Clients considered it important that the nurse recognizes each client's individual needs. The nurse was expected to perform duties efficiently, but in a calm and unrushed manner. A mechanic performance of tasks was considered negative. Humanity was viewed as a crucial element in the nurse-client relationship. Clients expressed their need to be seen as human beings. Seeing beyond the illness was considered important. A smiling nurse was described to be able to alleviate pain and anxiety. Clients hoped to have a close relationship with the nurse. The development of a close relationship was considered to be more likely if the nurse is familiar and genuine. Clients wish the nurses to have a more attending presence. Clients suggested that the work areas of the nurses could be limited so that they would have more time to transfer from one place to another. Clients felt that they would benefit from this as well. The nurses were expected to be more considerate. Clients wished for more information regarding changes that affect their care. They wished to be informed about changes in schedules and plans. Clients hoped for continuity from the nurse-client relationship. Considering the expectations of clients promotes client satisfaction. Home care providers have an opportunity to reflect their own care behaviour on the findings. To better meet the needs of the clients, nurses could apply the concept of loving-kindness in their work, and strive for a more attending presence.

Suorituskyvyn mittaaminen ja johtaminen henkilöstön näkökulmasta

Tämän tutkimuksen tavoitteena oli selvittää niitä tekijöitä, joihin yrityksen johdon tulisi kiinnittää huomiota suorituskykyä mitattaessa. Työssä tarkasteltiin tietämystä yrityksen suorituskyvystä, tavoitteista ja niiden mittaamisesta. Lisäksi tutkittiin yritysten sisäistä viestintää, päätöksentekoon vaikuttamista ja palkitsemista. Asioita tarkasteltiin eri ammattiasemissa olevien näkökulmista sekä esimiesaseman ja koulutustason suhteen. Tutkimuksen empiirinen aineisto kerättiin kyselylomakkeella kahdeksasta yrityksestä, vastauksia saatiin 210 kappaletta. Aineiston analysoinnissa käytettiin ristiintaulukointia ja -2- riippumattomuustestiä. Tutkimuksen tuloksena selvisi, että tieto omasta työstä ja sen tavoitteista on hyvällä tasolla. Henkilökohtaiseen kanssakäymiseen perustuvaa viestintää pidettiin parhaimpana. Omaan työhön ja tiimiin liittyvät päätökset olivat niitä, joihin haluttaisiin tulevaisuudessa vaikuttaa eniten. Palkitsemiskeinoista rahaa pidettiin parhaana, myös vapaa-aika ja kiitokset esimieheltä sekä työkaverilta miellyttivät vastaajia.

Supervised localimage feature detection

This thesis is about detection of local image features. The research topic belongs to the wider area of object detection, which is a machine vision and pattern recognition problem where an object must be detected (located) in an image. State-of-the-art object detection methods often divide the problem into separate interest point detection and local image description steps, but in this thesis a different technique is used, leading to higher quality image features which enable more precise localization. Instead of using interest point detection the landmark positions are marked manually. Therefore, the quality of the image features is not limited by the interest point detection phase and the learning of image features is simplified. The approach combines both interest point detection and local description into one phase for detection. Computational efficiency of the descriptor is therefore important, leaving out many of the commonly used descriptors as unsuitably heavy. Multiresolution Gabor features has been the main descriptor in this thesis and improving their efficiency is a significant part. Actual image features are formed from descriptors by using a classifierwhich can then recognize similar looking patches in new images. The main classifier is based on Gaussian mixture models. Classifiers are used in one-class classifier configuration where there are only positive training samples without explicit background class. The local image feature detection method has been tested with two freely available face detection databases and a proprietary license plate database. The localization performance was very good in these experiments. Other applications applying the same under-lying techniques are also presented, including object categorization and fault detection.

Local and Global Feature Extraction for Invariant Object Recognition

Perceiving the world visually is a basic act for humans, but for computers it is still an unsolved problem. The variability present innatural environments is an obstacle for effective computer vision. The goal of invariant object recognition is to recognise objects in a digital image despite variations in, for example, pose, lighting or occlusion. In this study, invariant object recognition is considered from the viewpoint of feature extraction. Thedifferences between local and global features are studied with emphasis on Hough transform and Gabor filtering based feature extraction. The methods are examined with respect to four capabilities: generality, invariance, stability, and efficiency. Invariant features are presented using both Hough transform and Gabor filtering. A modified Hough transform technique is also presented where the distortion tolerance is increased by incorporating local information. In addition, methods for decreasing the computational costs of the Hough transform employing parallel processing and local information are introduced.

The Changing Face of Psychiatric Nursing –Care or Control?

This report has been written as part of the project “Toward improved quality – developing nurse’s continuing vocational training in hospitals and inpatient units”. Its overall goal is to ensure high quality, ethically appropriate and therapeutically effective interventions to enable nurses to manage distressed and disturbed patients in European psychiatric hospitals and inpatient units. In this large-scale, multinational projects there are all together six European countries involved: Finland, Ireland, England, Portugal, Italy and Lithuania. The project work plan were during autumn 2006 and spring 2007. The content of this publication was produced in the first stage of the project aiming to collect the preliminary source material for the project. The literature review was carried out in the project stage, providing the groundwork for the next steps for the project. This project aims to develop an interactive multinational portal with training material. Therefore, it is important to share an understanding of basic information, psychiatric nurse’s continuing vocational education, laws and ethical codes and patient restriction used in mental health care. In this publication, the purpose of the material produced here is to understand nurses’ educational need related to vocational continuing education and to be used in further project stages as an empirical data collection. The data were collected as a preliminary source material for latter phases where nurse’s perceptions of the current practice, nurse’s attitudes to mental illness, prevalence of use of seclusion room and existing and desired vocational training provision will be collected in six different European countries. The following organisations are involved in this project: University of Turku, Dublin City University, St. Vincent Hospital, National Council for the Professional Development of Nursing and Midwifery, University of Padova, Klaipeda College - Health Faculty, Klaipeda Psychiatric Hospital, Escola Superior de Enfermagem de Lisboa, Centro Hospitalar Psiquiátrico de Lisboa, Omnia Vocational Institution the Espoo Region, Kellokoski psychiatric hospital, Hyvinkää hospital area, Pirkanmaa Hospital District, Kingston University & St. George’s Medical School and South West London & St. George’s Mental Health NHS Trust. A wide variety of different countries, organisations and individuals in this project give us a strong confidence that theoretical, practical, ethical and political issues around the topic of interest will be taken account during this project lifetime. We are aware the content of this book will be partially outdated almost as soon as it has been published. We still hope that this publication will encourage nurses and different professions working in mental health care field to have a basic understanding of similarities and differences between different European countries related in mental health care. We also hope that this publication will inspirate and motivate nurses in maintaining and developing the quality of psychiatric care in Europe.

Optical Character Recognition for Symbian OS

This Master's thesis addresses the design and implementation of the optical character recognition (OCR) system for a mobile device working on the Symbian operating system. The developed OCR system, named OCRCapriccio, emphasizes the modularity, effective extensibility and reuse. The system consists of two parts which are the graphical user interface and the OCR engine that was implemented as a plug-in. In fact, the plug-in includes two implementations of the OCR engine for enabling two types of recognition: the bitmap comparison based recognition and statistical recognition. The implementation results have shown that the approach based on bitmap comparison is more suitable for the Symbian environment because of its nature. Although the current implementation of bitmap comparison is lacking in accuracy, further development should be done in its direction. The biggest challenges of this work were related to developing an OCR scheme that would be suitable for Symbian OS Smartphones that have limited computational power and restricted resources.

Physical Realization of an Optical Automatic Target Recognition System

In the modern warfare there is an active development of a new trend connected with a robotic warfare. One of the critical elements of robotics warfare systems is an automatic target recognition system, allowing to recognize objects, based on the data received from sensors. This work considers aspects of optical realization of such a system by means of NIR target scanning at fixed wavelengths. An algorithm was designed, an experimental setup was built and samples of various modern gear and apparel materials were tested. For pattern testing the samples of actively arm engaged armies camouflages were chosen. Tests were performed both in clear atmosphere and in the artificial extremely humid and hot atmosphere to simulate field conditions.

External knowledge transfer mechanisms in service business acquisition

In knowledge-intensive economy an effective knowledge transfer is a part of the firm’s strategy to achieve a competitive advantage in the market. Knowledge transfer related to a variety of mechanisms depends on the nature of knowledge and context. The topic is, however, very little empirical studied and there is a research gap in scientific literature. This study examined and analyzed external knowledge transfer mechanisms in service business and especially in the context of acquisitions. The aim was to find out what kind of mechanisms was used when the buyer began to transfer data e.g. their own agendas and practices to the purchased units. Another major research goal was to identify the critical factors which contributed to knowledge transfer through different mechanisms. The study was conducted as a multiple-case study in a consultative service business company, in its four business units acquired by acquisition, in various parts of the country. The empirical part of the study was carried out as focus group interviews in each unit, and the data were analyzed using qualitative methods. The main findings of this study were firstly the nine different knowledge transfer mechanisms in service business acquisition: acquisition management team as an initiator, unit manager as a translator, formal training, self-directed learning, rooming-in, IT systems implementation, customer relationship management, codified database and ecommunication. The used mechanisms brought up several aspects as giving the face to changing, security of receiving right knowledge and correctly interpreted we-ness atmosphere, and orientation to use more consultative touch with customers. The study pointed out seven critical factors contributed to different mechanisms: absorption, motivation, organizational learning, social interaction, trust, interpretation and time resource. The two last mentioned were new findings compared to previous studies. Each of the mechanisms and the related critical factors contributed in different ways to the activity in different units after the acquisition. The role of knowledge management strategy was the most significant managerial contribution of the study. Phenomenon is not recognized enough although it is strongly linked in knowledge based companies. The recognition would help to develop a better understanding of the business through acquisitions, especially in situations such as where two different knowledge strategies combines in new common company.

Evaluation of Bubble Formation and Break Up in Suppression Pools by Using Pattern Recognition Methods

During a possible loss of coolant accident in BWRs, a large amount of steam will be released from the reactor pressure vessel to the suppression pool. Steam will be condensed into the suppression pool causing dynamic and structural loads to the pool. The formation and break up of bubbles can be measured by visual observation using a suitable pattern recognition algorithm. The aim of this study was to improve the preliminary pattern recognition algorithm, developed by Vesa Tanskanen in his doctoral dissertation, by using MATLAB. Video material from the PPOOLEX test facility, recorded during thermal stratification and mixing experiments, was used as a reference in the development of the algorithm. The developed algorithm consists of two parts: the pattern recognition of the bubbles and the analysis of recognized bubble images. The bubble recognition works well, but some errors will appear due to the complex structure of the pool. The results of the image analysis were reasonable. The volume and the surface area of the bubbles were not evaluated. Chugging frequencies calculated by using FFT fitted well into the results of oscillation frequencies measured in the experiments. The pattern recognition algorithm works in the conditions it is designed for. If the measurement configuration will be changed, some modifications have to be done. Numerous improvements are proposed for the future 3D equipment.

Bay of Bengal : a survey of the sea face of the Soondurbuns

Kartta kuuluu A. E. Nordenskiöldin kokoelmaan

Semantic and fuzzy modelling for human behaviour recognition in smart spaces : a case study on ambient assisted living.

Human activity recognition in everyday environments is a critical, but challenging task in Ambient Intelligence applications to achieve proper Ambient Assisted Living, and key challenges still remain to be dealt with to realize robust methods. One of the major limitations of the Ambient Intelligence systems today is the lack of semantic models of those activities on the environment, so that the system can recognize the speci c activity being performed by the user(s) and act accordingly. In this context, this thesis addresses the general problem of knowledge representation in Smart Spaces. The main objective is to develop knowledge-based models, equipped with semantics to learn, infer and monitor human behaviours in Smart Spaces. Moreover, it is easy to recognize that some aspects of this problem have a high degree of uncertainty, and therefore, the developed models must be equipped with mechanisms to manage this type of information. A fuzzy ontology and a semantic hybrid system are presented to allow modelling and recognition of a set of complex real-life scenarios where vagueness and uncertainty are inherent to the human nature of the users that perform it. The handling of uncertain, incomplete and vague data (i.e., missing sensor readings and activity execution variations, since human behaviour is non-deterministic) is approached for the rst time through a fuzzy ontology validated on real-time settings within a hybrid data-driven and knowledgebased architecture. The semantics of activities, sub-activities and real-time object interaction are taken into consideration. The proposed framework consists of two main modules: the low-level sub-activity recognizer and the high-level activity recognizer. The rst module detects sub-activities (i.e., actions or basic activities) that take input data directly from a depth sensor (Kinect). The main contribution of this thesis tackles the second component of the hybrid system, which lays on top of the previous one, in a superior level of abstraction, and acquires the input data from the rst module's output, and executes ontological inference to provide users, activities and their in uence in the environment, with semantics. This component is thus knowledge-based, and a fuzzy ontology was designed to model the high-level activities. Since activity recognition requires context-awareness and the ability to discriminate among activities in di erent environments, the semantic framework allows for modelling common-sense knowledge in the form of a rule-based system that supports expressions close to natural language in the form of fuzzy linguistic labels. The framework advantages have been evaluated with a challenging and new public dataset, CAD-120, achieving an accuracy of 90.1% and 91.1% respectively for low and high-level activities. This entails an improvement over both, entirely data-driven approaches, and merely ontology-based approaches. As an added value, for the system to be su ciently simple and exible to be managed by non-expert users, and thus, facilitate the transfer of research to industry, a development framework composed by a programming toolbox, a hybrid crisp and fuzzy architecture, and graphical models to represent and con gure human behaviour in Smart Spaces, were developed in order to provide the framework with more usability in the nal application. As a result, human behaviour recognition can help assisting people with special needs such as in healthcare, independent elderly living, in remote rehabilitation monitoring, industrial process guideline control, and many other cases. This thesis shows use cases in these areas.

Automatic recognition of fish from video sequences

The problem of automatic recognition of the fish from the video sequences is discussed in this Master’s Thesis. This is a very urgent issue for many organizations engaged in fish farming in Finland and Russia because the process of automation control and counting of individual species is turning point in the industry. The difficulties and the specific features of the problem have been identified in order to find a solution and propose some recommendations for the components of the automated fish recognition system. Methods such as background subtraction, Kalman filtering and Viola-Jones method were implemented during this work for detection, tracking and estimation of fish parameters. Both the results of the experiments and the choice of the appropriate methods strongly depend on the quality and the type of a video which is used as an input data. Practical experiments have demonstrated that not all methods can produce good results for real data, whereas on synthetic data they operate satisfactorily.

Recognition of nucleic acids by metal ion complexes

Metal-ion-mediated base-pairing of nucleic acids has attracted considerable attention during the past decade, since it offers means to expand the genetic code by artificial base-pairs, to create predesigned molecular architecture by metal-ion-mediated inter- or intra-strand cross-links, or to convert double stranded DNA to a nano-scale wire. Such applications largely depend on the presence of a modified nucleobase in both strands engaged in the duplex formation. Hybridization of metal-ion-binding oligonucleotide analogs with natural nucleic acid sequences has received much less attention in spite of obvious applications. While the natural oligonucleotides hybridize with high selectivity, their affinity for complementary sequences is inadequate for a number of applications. In the case of DNA, for example, more than 10 consecutive Watson-Crick base pairs are required for a stable duplex at room temperature, making targeting of sequences shorter than this challenging. For example, many types of cancer exhibit distinctive profiles of oncogenic miRNA, the diagnostics of which is, however, difficult owing to the presence of only short single stranded loop structures. Metallo-oligonucleotides, with their superior affinity towards their natural complements, would offer a way to overcome the low stability of short duplexes. In this study a number of metal-ion-binding surrogate nucleosides were prepared and their interaction with nucleoside 5´-monophosphates (NMPs) has been investigated by 1H NMR spectroscopy. To find metal ion complexes that could discriminate between natural nucleobases upon double helix formation, glycol nucleic acid (GNA) sequences carrying a PdII ion with vacant coordination sites at a predetermined position were synthesized and their affinity to complementary as well as mismatched counterparts quantified by UV-melting measurements.