The Learning Affect Monitor (LAM) - A computer-based system integrating quantitative and qualitative assessment of affective states in daily life.

The Learning Affect Monitor (LAM) is a new computer-based assessment system integrating basic dimensional evaluation and discrete description of affective states in daily life, based on an autonomous adapting system. Subjects evaluate their affective states according to a tridimensional space (valence and activation circumplex as well as global intensity) and then qualify it using up to 30 adjective descriptors chosen from a list. The system gradually adapts to the user, enabling the affect descriptors it presents to be increasingly relevant. An initial study with 51 subjects, using a 1 week time-sampling with 8 to 10 randomized signals per day, produced n = 2,813 records with good reliability measures (e.g., response rate of 88.8%, mean split-half reliability of .86), user acceptance, and usability. Multilevel analyses show circadian and hebdomadal patterns, and significant individual and situational variance components of the basic dimension evaluations. Validity analyses indicate sound assignment of qualitative affect descriptors in the bidimensional semantic space according to the circumplex model of basic affect dimensions. The LAM assessment module can be implemented on different platforms (palm, desk, mobile phone) and provides very rapid and meaningful data collection, preserving complex and interindividually comparable information in the domain of emotion and well-being.

Implementation of an Integrated Activity-Based Costing in a Holistic Database Management System and its Implications for Operations Management

Diplomityössä on tutkittu reaaliaikaisen toimintolaskennan toteuttamista suomalaisen lasersiruja valmistavan PK-yrityksen tietojärjestelmään. Lisäksi on tarkasteltu toimintolaskennan vaikutuksia operatiiviseen toimintaan sekä toimintojen johtamiseen. Työn kirjallisuusosassa on käsitelty kirjallisuuslähteiden perusteella toimintolaskennan teorioita, laskentamenetelmiä sekä teknisessä toteutuksessa käytettyjä teknologioita. Työn toteutusosassa suunniteltiin ja toteutettiin WWW-pohjainen toimintolaskentajärjestelmä case-yrityksen kustannuslaskennan sekä taloushallinnon avuksi. Työkalu integroitiin osaksi yrityksen toiminnanohjaus- sekä valmistuksenohjausjärjestelmää. Perinteisiin toimintolaskentamallien tiedonkeruujärjestelmiin verrattuna case-yrityksessä syötteet toimintolaskentajärjestelmälle tulevat reaaliaikaisesti osana suurempaa tietojärjestelmäintegraatiota.Diplomityö pyrkii luomaan suhteen toimintolaskennan vaatimusten ja tietokantajärjestelmien välille. Toimintolaskentajärjestelmää yritys voi hyödyntää esimerkiksi tuotteiden hinnoittelussa ja kustannuslaskennassa näkemällä tuotteisiin liittyviä kustannuksia eri näkökulmista. Päätelmiä voidaan tehdä tarkkaan kustannusinformaatioon perustuen sekä määrittää järjestelmän tuottaman datan perusteella, onko tietyn projektin, asiakkuuden tai tuotteen kehittäminen taloudellisesti kannattavaa.

A definition and classification of status epilepticus - Report of the ILAE Task Force on Classification of Status Epilepticus.

The Commission on Classification and Terminology and the Commission on Epidemiology of the International League Against Epilepsy (ILAE) have charged a Task Force to revise concepts, definition, and classification of status epilepticus (SE). The proposed new definition of SE is as follows: Status epilepticus is a condition resulting either from the failure of the mechanisms responsible for seizure termination or from the initiation of mechanisms, which lead to abnormally, prolonged seizures (after time point t1 ). It is a condition, which can have long-term consequences (after time point t2 ), including neuronal death, neuronal injury, and alteration of neuronal networks, depending on the type and duration of seizures. This definition is conceptual, with two operational dimensions: the first is the length of the seizure and the time point (t1 ) beyond which the seizure should be regarded as "continuous seizure activity." The second time point (t2 ) is the time of ongoing seizure activity after which there is a risk of long-term consequences. In the case of convulsive (tonic-clonic) SE, both time points (t1 at 5 min and t2 at 30 min) are based on animal experiments and clinical research. This evidence is incomplete, and there is furthermore considerable variation, so these time points should be considered as the best estimates currently available. Data are not yet available for other forms of SE, but as knowledge and understanding increase, time points can be defined for specific forms of SE based on scientific evidence and incorporated into the definition, without changing the underlying concepts. A new diagnostic classification system of SE is proposed, which will provide a framework for clinical diagnosis, investigation, and therapeutic approaches for each patient. There are four axes: (1) semiology; (2) etiology; (3) electroencephalography (EEG) correlates; and (4) age. Axis 1 (semiology) lists different forms of SE divided into those with prominent motor systems, those without prominent motor systems, and currently indeterminate conditions (such as acute confusional states with epileptiform EEG patterns). Axis 2 (etiology) is divided into subcategories of known and unknown causes. Axis 3 (EEG correlates) adopts the latest recommendations by consensus panels to use the following descriptors for the EEG: name of pattern, morphology, location, time-related features, modulation, and effect of intervention. Finally, axis 4 divides age groups into neonatal, infancy, childhood, adolescent and adulthood, and elderly.

Incorporating complex cells into neural networks for pattern classification

Dans le domaine des neurosciences computationnelles, l'hypothèse a été émise que le système visuel, depuis la rétine et jusqu'au cortex visuel primaire au moins, ajuste continuellement un modèle probabiliste avec des variables latentes, à son flux de perceptions. Ni le modèle exact, ni la méthode exacte utilisée pour l'ajustement ne sont connus, mais les algorithmes existants qui permettent l'ajustement de tels modèles ont besoin de faire une estimation conditionnelle des variables latentes. Cela nous peut nous aider à comprendre pourquoi le système visuel pourrait ajuster un tel modèle; si le modèle est approprié, ces estimé conditionnels peuvent aussi former une excellente représentation, qui permettent d'analyser le contenu sémantique des images perçues. Le travail présenté ici utilise la performance en classification d'images (discrimination entre des types d'objets communs) comme base pour comparer des modèles du système visuel, et des algorithmes pour ajuster ces modèles (vus comme des densités de probabilité) à des images. Cette thèse (a) montre que des modèles basés sur les cellules complexes de l'aire visuelle V1 généralisent mieux à partir d'exemples d'entraînement étiquetés que les réseaux de neurones conventionnels, dont les unités cachées sont plus semblables aux cellules simples de V1; (b) présente une nouvelle interprétation des modèles du système visuels basés sur des cellules complexes, comme distributions de probabilités, ainsi que de nouveaux algorithmes pour les ajuster à des données; et (c) montre que ces modèles forment des représentations qui sont meilleures pour la classification d'images, après avoir été entraînés comme des modèles de probabilités. Deux innovations techniques additionnelles, qui ont rendu ce travail possible, sont également décrites : un algorithme de recherche aléatoire pour sélectionner des hyper-paramètres, et un compilateur pour des expressions mathématiques matricielles, qui peut optimiser ces expressions pour processeur central (CPU) et graphique (GPU).

Development of a Biometric Personal Authentication System Based on Fingerprint and Speech

Biometrics deals with the physiological and behavioral characteristics of an individual to establish identity. Fingerprint based authentication is the most advanced biometric authentication technology. The minutiae based fingerprint identification method offer reasonable identification rate. The feature minutiae map consists of about 70-100 minutia points and matching accuracy is dropping down while the size of database is growing up. Hence it is inevitable to make the size of the fingerprint feature code to be as smaller as possible so that identification may be much easier. In this research, a novel global singularity based fingerprint representation is proposed. Fingerprint baseline, which is the line between distal and intermediate phalangeal joint line in the fingerprint, is taken as the reference line. A polygon is formed with the singularities and the fingerprint baseline. The feature vectors are the polygonal angle, sides, area, type and the ridge counts in between the singularities. 100% recognition rate is achieved in this method. The method is compared with the conventional minutiae based recognition method in terms of computation time, receiver operator characteristics (ROC) and the feature vector length. Speech is a behavioural biometric modality and can be used for identification of a speaker. In this work, MFCC of text dependant speeches are computed and clustered using k-means algorithm. A backpropagation based Artificial Neural Network is trained to identify the clustered speech code. The performance of the neural network classifier is compared with the VQ based Euclidean minimum classifier. Biometric systems that use a single modality are usually affected by problems like noisy sensor data, non-universality and/or lack of distinctiveness of the biometric trait, unacceptable error rates, and spoof attacks. Multifinger feature level fusion based fingerprint recognition is developed and the performances are measured in terms of the ROC curve. Score level fusion of fingerprint and speech based recognition system is done and 100% accuracy is achieved for a considerable range of matching threshold

A dynamic knowledge-based decision support system to handle solids separation problems in activated sludge systems: development and validation

El sistema de fangs activats és el tractament biològic més àmpliament utilitzat arreu del món per la depuració d'aigües residuals. El seu funcionament depèn de la correcta operació tant del reactor biològic com del decantador secundari. Quan la fase de sedimentació no es realitza correctament, la biomassa no decantada s'escapa amb l'efluent causant un impacte sobre el medi receptor. Els problemes de separació de sòlids, són actualment una de les principals causes d'ineficiència en l'operació dels sistemes de fangs activats arreu del món. Inclouen: bulking filamentós, bulking viscós, escumes biològiques, creixement dispers, flòcul pin-point i desnitrificació incontrolada. L'origen dels problemes de separació generalment es troba en un desequilibri entre les principals comunitats de microorganismes implicades en la sedimentació de la biomassa: els bacteris formadors de flòcul i els bacteris filamentosos. Degut a aquest origen microbiològic, la seva identificació i control no és una tasca fàcil pels caps de planta. Els Sistemes de Suport a la Presa de Decisions basats en el coneixement (KBDSS) són un grup d'eines informàtiques caracteritzades per la seva capacitat de representar coneixement heurístic i tractar grans quantitats de dades. L'objectiu de la present tesi és el desenvolupament i validació d'un KBDSS específicament dissenyat per donar suport als caps de planta en el control dels problemes de separació de sòlids d'orígen microbiològic en els sistemes de fangs activats. Per aconseguir aquest objectiu principal, el KBDSS ha de presentar les següents característiques: (1) la implementació del sistema ha de ser viable i realista per garantir el seu correcte funcionament; (2) el raonament del sistema ha de ser dinàmic i evolutiu per adaptar-se a les necessitats del domini al qual es vol aplicar i (3) el raonament del sistema ha de ser intel·ligent. En primer lloc, a fi de garantir la viabilitat del sistema, s'ha realitzat un estudi a petita escala (Catalunya) que ha permès determinar tant les variables més utilitzades per a la diagnosi i monitorització dels problemes i els mètodes de control més viables, com la detecció de les principals limitacions que el sistema hauria de resoldre. Els resultats d'anteriors aplicacions han demostrat que la principal limitació en el desenvolupament de KBDSSs és l'estructura de la base de coneixement (KB), on es representa tot el coneixement adquirit sobre el domini, juntament amb els processos de raonament a seguir. En el nostre cas, tenint en compte la dinàmica del domini, aquestes limitacions es podrien veure incrementades si aquest disseny no fos òptim. En aquest sentit, s'ha proposat el Domino Model com a eina per dissenyar conceptualment el sistema. Finalment, segons el darrer objectiu referent al seguiment d'un raonament intel·ligent, l'ús d'un Sistema Expert (basat en coneixement expert) i l'ús d'un Sistema de Raonament Basat en Casos (basat en l'experiència) han estat integrats com els principals sistemes intel·ligents encarregats de dur a terme el raonament del KBDSS. Als capítols 5 i 6 respectivament, es presenten el desenvolupament del Sistema Expert dinàmic (ES) i del Sistema de Raonament Basat en Casos temporal, anomenat Sistema de Raonament Basat en Episodis (EBRS). A continuació, al capítol 7, es presenten detalls de la implementació del sistema global (KBDSS) en l'entorn G2. Seguidament, al capítol 8, es mostren els resultats obtinguts durant els 11 mesos de validació del sistema, on aspectes com la precisió, capacitat i utilitat del sistema han estat validats tant experimentalment (prèviament a la implementació) com a partir de la seva implementació real a l'EDAR de Girona. Finalment, al capítol 9 s'enumeren les principals conclusions derivades de la present tesi.

A camera based digit location and recognition system for garment tracking

Garment information tracking is required for clean room garment management. In this paper, we present a camera-based robust system with implementation of Optical Character Reconition (OCR) techniques to fulfill garment label recognition. In the system, a camera is used for image capturing; an adaptive thresholding algorithm is employed to generate binary images; Connected Component Labelling (CCL) is then adopted for object detection in the binary image as a part of finding the ROI (Region of Interest); Artificial Neural Networks (ANNs) with the BP (Back Propagation) learning algorithm are used for digit recognition; and finally the system is verified by a system database. The system has been tested. The results show that it is capable of coping with variance of lighting, digit twisting, background complexity, and font orientations. The system performance with association to the digit recognition rate has met the design requirement. It has achieved real-time and error-free garment information tracking during the testing.

A continuous wavelet transform and classification method for delirium motoric subtyping

The usefulness of motor subtypes of delirium is unclear due to inconsistency in subtyping methods and a lack of validation with objective measures of activity. The activity of 40 patients was measured over 24 h with a discrete accelerometer-based activity monitor. The continuous wavelet transform (CWT) with various mother wavelets were applied to accelerometry data from three randomly selected patients with DSM-IV delirium that were readily divided into hyperactive, hypoactive, and mixed motor subtypes. A classification tree used the periods of overall movement as measured by the discrete accelerometer-based monitor as determining factors for which to classify these delirious patients. This data used to create the classification tree were based upon the minimum, maximum, standard deviation, and number of coefficient values, generated over a range of scales by the CWT. The classification tree was subsequently used to define the remaining motoric subtypes. The use of a classification system shows how delirium subtypes can be categorized in relation to overall motoric behavior. The classification system was also implemented to successfully define other patient motoric subtypes. Motor subtypes of delirium defined by observed ward behavior differ in electronically measured activity levels.

Multi-agent based modeling and simulation of complex system in hospital

This study puts forward a method to model and simulate the complex system of hospital on the basis of multi-agent technology. The formation of the agents of hospitals with intelligent and coordinative characteristics was designed, the message object was defined, and the model operating mechanism of autonomous activities and coordination mechanism was also designed. In addition, the Ontology library and Norm library etc. were introduced using semiotic method and theory, to enlarge the method of system modelling. Swarm was used to develop the multi-agent based simulation system, which is favorable for making guidelines for hospital's improving it's organization and management, optimizing the working procedure, improving the quality of medical care as well as reducing medical charge costs.

Palaeovegetation in China during the late Quaternary: Biome reconstructions based on a global scheme of plant functional types

Two previous reconstructions of palaeovegetation across the whole of China were performed using a simple classification of plant functional types (PFTs). Now a more explicit, global PFT classification scheme has been developed, and a substantial number of additional pollen records have become available. Here we apply the global scheme of PFTs to a comprehensive set of pollen records available from China to test the applicability of the global scheme of PFTs in China, and to obtain a well-founded reconstruction of changing palaeovegetation patterns. A total of 806 pollen surface samples, 188 mid-Holocene (MH, 6000 14C yr BP) and 50 last glacial maximum (LGM, 18,000 14C yr BP) pollen records were used to reconstruct vegetation patterns in China, based on a new global classification system of PFTs and a standard numerical technique for biome assignment (biomization). The biome reconstruction based on pollen surface samples showed convincing agreement with present potential natural vegetation. Coherent patterns of change in biome distribution between MH, LGM and present are observed. In the MH, cold and cool-temperate evergreen needleleaf forests and mixed forests, temperate deciduous broadleaf forest, and warm-temperate evergreen broadleaf and mixed forest in eastern China were shifted northward by 200–500 km. Cold-deciduous forest in northeastern China was replaced by cold evergreen needleleaf forest while in central northern China, cold-deciduous forest was present at some sites now occupied by temperate grassland and desert. The forest–grassland boundary was 200–300 km west of its present position. Temperate xerophytic shrubland, temperate grassland and desert covered a large area on the Tibetan Plateau, but the area of tundra was reduced. Treeline was 300–500 m higher than present in Tibet. These changes imply generally warmer winters, longer growing seasons and more precipitation during the MH. Westward shifts of the forest–shrubland–grassland and grassland–desert boundaries imply greater moisture availability in the MH, consistent with a stronger summer monsoon. During the LGM, in contrast, cold-deciduous forest, cool-temperate evergreen needleleaf forest, cool mixed forests, warm-temperate evergreen broadleaf and mixed forest in eastern China were displaced to the south by 300–1000 km, while temperate deciduous broadleaf forest, pure warm-temperate evergreen forest, tropical semi-evergreen and evergreen broadleaf forests were restricted or absent from the mainland of southern China, implying colder winters than present. Strong shifts of temperate xerophytic shrubland, temperate grassland and desert to the south and east in northern and western China and on the Tibetan Plateau imply drier conditions than present.

Array based detection of antibiotic resistance genes in Gram negative bacteria isolated from retail poultry meat in the UK and Ireland

The use of antibiotics in birds and animals intended for human consumption within the European Union (EU) and elsewhere has been subject to regulation prohibiting the use of antimicrobials as growth promoters and the use of last resort antibiotics in an attempt to reduce the spread of multi-resistant Gram negative bacteria. Given the inexorable spread of antibiotic resistance there is an increasing need for improved monitoring of our food. Using selective media, Gram negative bacteria were isolated from retail chicken of UK-Intensively reared (n = 27), Irish-Intensively reared (n = 19) and UK-Free range (n = 30) origin and subjected to an oligonucleotide based array system for the detection of 47 clinically relevant antibiotic resistance genes (ARGs) and two integrase genes. High incidences of β-lactamase genes were noted in all sample types, acc (67%), cmy (80%), fox (55%) and tem (40%) while chloramphenicol resistant determinants were detected in bacteria from the UK poultry portions and were absent in bacteria from the Irish samples. Denaturing Gradient Gel Electrophoresis (DGGE) was used to qualitatively analyse the Gram negative population in the samples and showed the expected diversity based on band stabbing and DNA sequencing. The array system proved to be a quick method for the detection of antibiotic resistance gene (ARG) burden within a mixed Gram negative bacterial population.

Power performance evaluation of an electric home fan with triac-based automatic speed control system

In order to provide a low cost system of thermal comfort, a common model of home fan, 40 cm diameter size, had its manual four-button control system replaced by an automatic speed control. The new control system has a temperature sensor feeding a microcontroller that, by using an optic coupling, DIAC or TRIAC-based circuit, varies the RMS value of the fan motor input voltage and its speed, according to the room temperature. Over a wide range of velocity, the fan net power and the motor fan input power were measured working under both control system. The temperature of the motor stator and the voltage waveforms were observed too. Measured values analysis showed that the TRIAC-based control system makes the fan motor work at a very low power factor and efficiency values. The worst case is at low velocity range where the higher fan motor stator temperatures were registered. The poor power factor and efficiency and the harmonics signals inserted in the motor input voltage wave by the TRIAC commutation procedure are correlated.

Development of an open case-based decision-support system for diagnosis in oral pathology

Making diagnoses in oral pathology are often difficult and confusing in dental practice, especially for the lessexperienced dental student. One of the most promising areas in bioinformatics is computer-aided diagnosis, where a computer system is capable of imitating human reasoning ability and provides diagnoses with an accuracy approaching that of expert professionals. This type of system could be an alternative tool for assisting dental students to overcome the difficulties of the oral pathology learning process. This could allow students to define variables and information, important to improving the decision-making performance. However, no current open data management system has been integrated with an artificial intelligence system in a user-friendly environment. Such a system could also be used as an education tool to help students perform diagnoses. The aim of the present study was to develop and test an open case-based decisionsupport system.Methods: An open decision-support system based on Bayes' theorem connected to a relational database was developed using the C++ programming language. The software was tested in the computerisation of a surgical pathology service and in simulating the diagnosis of 43 known cases of oral bone disease. The simulation was performed after the system was initially filled with data from 401 cases of oral bone disease.Results: the system allowed the authors to construct and to manage a pathology database, and to simulate diagnoses using the variables from the database.Conclusion: Combining a relational database and an open decision-support system in the same user-friendly environment proved effective in simulating diagnoses based on information from an updated database.

Inland waterways classification as a tool for public policy and planning: core concepts and proposals for South America

This FAL Bulletin looks at the classification of navigable inland waterways in South America. It describes an existing classification system (ECMT/UNECE), noting its role in the development of river transport, based on which it discusses lessons learned and presents a preliminary proposal for a classification for South America.

Automatic classification of prostate stromal tissue in histological images using Haralick descriptors and Local Binary Patterns

In this paper we presente a classification system that uses a combination of texture features from stromal regions: Haralick features and Local Binary Patterns (LBP) in wavelet domain. The system has five steps for classification of the tissues. First, the stromal regions were detected and extracted using segmentation techniques based on thresholding and RGB colour space. Second, the Wavelet decomposition was applied in the extracted regions to obtain the Wavelet coefficients. Third, the Haralick and LBP features were extracted from the coefficients. Fourth, relevant features were selected using the ANOVA statistical method. The classication (fifth step) was performed with Radial Basis Function (RBF) networks. The system was tested in 105 prostate images, which were divided into three groups of 35 images: normal, hyperplastic and cancerous. The system performance was evaluated using the area under the ROC curve and resulted in 0.98 for normal versus cancer, 0.95 for hyperplasia versus cancer and 0.96 for normal versus hyperplasia. Our results suggest that texture features can be used as discriminators for stromal tissues prostate images. Furthermore, the system was effective to classify prostate images, specially the hyperplastic class which is the most difficult type in diagnosis and prognosis.