Phylogenetic relationships among Trichodinidae (Ciliophora : Peritricha) derived from the characteristic values of denticles

The phylogenetic relationships among trichodinids remain obscure. As an important diagnostic marker, the morphology of the denticles in the adhesive disc as well as the adoral spiral has been widely used in generic discrimination and species identification of trichodinids. We studied the characters of denticles of the ten genera of Trichodinidae and the sole genus Urceolaria of Urceolariidae by using a quantitative method. The characteristic values were used to generate Manhattan distance, on which the dendrogram was based to construct with the Unweighted Paired Group Method using the Arithmetic mean (UPGMA). The investigations show that all the genera of the family Trichodinidae were clearly separate from the outgroup Urceolaria, and within the Trichodinidae: (i) Dipartiella grouped with Trichodinella and Tripartiella and lay in the closest position to the outgroup with a low dissimilarity, suggesting Dipartiella might be the most primitive genus in the family; (ii) Hemitrichodina clustered in a single clad and lay in the farthest position to the outgroup with the highest dissimilarity, indicating that it might be the most advanced genus; and (iii) the other 6 genera, Trichodina, Paratrichodina, Semitrichodina, Vauchomia, Pallitrichodina and Trichodoxa clustered in a big clad with very low dissimilarity, showing that they are closely related to each other. We discuss the evolutionary trend of the denticle and conclude that the denticles of the adhesive disc should be an apomorphic feature of the trichodinids and their changes could reflect the evolutionary tendencies of these ciliates.

BoostMap: A Method for Efficient Approximate Similarity Rankings

This paper introduces BoostMap, a method that can significantly reduce retrieval time in image and video database systems that employ computationally expensive distance measures, metric or non-metric. Database and query objects are embedded into a Euclidean space, in which similarities can be rapidly measured using a weighted Manhattan distance. Embedding construction is formulated as a machine learning task, where AdaBoost is used to combine many simple, 1D embeddings into a multidimensional embedding that preserves a significant amount of the proximity structure in the original space. Performance is evaluated in a hand pose estimation system, and a dynamic gesture recognition system, where the proposed method is used to retrieve approximate nearest neighbors under expensive image and video similarity measures. In both systems, BoostMap significantly increases efficiency, with minimal losses in accuracy. Moreover, the experiments indicate that BoostMap compares favorably with existing embedding methods that have been employed in computer vision and database applications, i.e., FastMap and Bourgain embeddings.

Learning Euclidean Embeddings for Indexing and Classification

BoostMap is a recently proposed method for efficient approximate nearest neighbor retrieval in arbitrary non-Euclidean spaces with computationally expensive and possibly non-metric distance measures. Database and query objects are embedded into a Euclidean space, in which similarities can be rapidly measured using a weighted Manhattan distance. The key idea is formulating embedding construction as a machine learning task, where AdaBoost is used to combine simple, 1D embeddings into a multidimensional embedding that preserves a large amount of the proximity structure of the original space. This paper demonstrates that, using the machine learning formulation of BoostMap, we can optimize embeddings for indexing and classification, in ways that are not possible with existing alternatives for constructive embeddings, and without additional costs in retrieval time. First, we show how to construct embeddings that are query-sensitive, in the sense that they yield a different distance measure for different queries, so as to improve nearest neighbor retrieval accuracy for each query. Second, we show how to optimize embeddings for nearest neighbor classification tasks, by tuning them to approximate a parameter space distance measure, instead of the original feature-based distance measure.

ZIL: An Energy-Efficient Indoor Localization System Using ZigBee Radio to Detect WiFi Fingerprints

In existing WiFi-based localization methods, smart mobile devices consume quite a lot of power as WiFi interfaces need to be used for frequent AP scanning during the localization process. In this work, we design an energy-efficient indoor localization system called ZigBee assisted indoor localization (ZIL) based on WiFi fingerprints via ZigBee interference signatures. ZIL uses ZigBee interfaces to collect mixed WiFi signals, which include non-periodic WiFi data and periodic beacon signals. However, WiFi APs cannot be identified from these WiFi signals by ZigBee interfaces directly. To address this issue, we propose a method for detecting WiFi APs to form WiFi fingerprints from the signals collected by ZigBee interfaces. We propose a novel fingerprint matching algorithm to align a pair of fingerprints effectively. To improve the localization accuracy, we design the K-nearest neighbor (KNN) method with three different weighted distances and find that the KNN algorithm with the Manhattan distance performs best. Experiments show that ZIL can achieve the localization accuracy of 87%, which is competitive compared to state-of-the-art WiFi fingerprint-based approaches, and save energy by 68% on average compared to the approach based on WiFi interface.

Clustering aplicado à Bolsa de Valores de Lisboa

O objetivo desta dissertação foi estudar um conjunto de empresas cotadas na bolsa de valores de Lisboa, para identificar aquelas que têm um comportamento semelhante ao longo do tempo. Para isso utilizamos algoritmos de Clustering tais como K-Means, PAM, Modelos hierárquicos, Funny e C-Means tanto com a distância euclidiana como com a distância de Manhattan. Para selecionar o melhor número de clusters identificado por cada um dos algoritmos testados, recorremos a alguns índices de avaliação/validação de clusters como o Davies Bouldin e Calinski-Harabasz entre outros.

La route qui mène au crime : déterminants de la mobilité des infracteurs de Gatineau en 2006

Cette étude porte sur la distance parcourue pour commettre un crime à Gatineau en 2006. Peu d’études canadiennes récentes ont porté sur le sujet. De plus, il existe un vide de connaissances sur la mobilité des délinquants dans les petites villes et les banlieues. La présente recherche vise à comparer trois mesures de distance différentes, à vérifier si la distance parcourue varie en fonction du type de crime et à voir si les variables de temps (jour de la semaine, moment de la journée et saison) de même que certaines caractéristiques des suspects (âge, sexe et lieu de résidence) ont un impact sur la distance parcourue. Pour chaque crime, l’adresse du suspect et le lieu du crime ont été géocodées pour ensuite calculer la distance entre les deux points. Il ressort de l’analyse de la forme des courbes de distances que seules les agressions sexuelles présentent une zone tampon. Les résultats des analyses statistiques indiquent que les jeunes sont plus mobiles que les suspects plus âgés et que les hommes parcourent une distance plus élevée que les femmes. Étonnement, la distance parcourue ne diffère pas significativement selon la saison et le moment de la journée. Enfin, comparativement aux autres criminels, les délinquants qui ont commis un vol qualifié sont ceux qui ont parcouru les plus grandes distances.

Aninhamento em redes bipartidas

We present a nestedness index that measures the nestedness pattern of bipartite networks, a problem that arises in theoretical ecology. Our measure is derived using the sum of distances of the occupied elements in the adjacency matrix of the network. This index quantifies directly the deviation of a given matrix from the nested pattern. In the most simple case the distance of the matrix element ai,j is di,j = i+j, the Manhattan distance. A generic distance is obtained as di,j = (i¬ + j¬)1/¬. The nestedness índex is defined by = 1 − where is the temperature of the matrix. We construct the temperature index using two benchmarks: the distance of the complete nested matrix that corresponds to zero temperature and the distance of the average random matrix that is defined as temperature one. We discuss an important feature of the problem: matrix occupancy. We address this question using a metric index ¬ that adjusts for matrix occupancy

Procedimiento multicriterio-multiobjetivo de planificación energética a comunidades rurales aisladas

La toma de decisiones en el sector energético se torna compleja frente a las disímiles opciones y objetivos a cumplir. Para minimizar esta complejidad, se han venido desarrollando una gama amplia de métodos de apoyo a la toma de decisiones en proyectos energéticos. En la última década, las energización de comunidades rurales aisladas ha venido siendo prioridad de muchos gobiernos para mitigar las migraciones del campo para la ciudad. Para la toma de decisiones en los proyectos energéticos de comunidades rurales aisladas se necesitan proyectar la influencia que estos tendrás sobre los costes económicos, medioambientales y sociales. Es por esta razón que el presente trabajo tuvo como objetivo diseñar un modelo original denominado Generación Energética Autóctona Y Limpia (GEAYL) aplicado a una comunidad rural aislada de la provincia de Granma en Cuba. Este modelo parte dos modelos que le preceden el PAMER y el SEMA. El modelo GEAYL constituye un procedimiento multicriterio-multiobjetivo de apoyo a la planificación energética para este contexto. Se plantearon cinco funciones objetivos: F1, para la minimización de los costes energéticos; F2 para la minimización de las emisiones de CO2, F3, para la minimización de las emisiones de NOx; F4, para la minimización de las emisiones de SOx (cuyos coeficientes fueron obtenidos a través de la literatura especializada) y F5, para la maximización de la Aceptación Social de la Energía. La función F5 y la manera de obtener sus coeficientes constituye la novedad del presente trabajo. Estos coeficientes se determinaron aplicando el método AHP (Proceso Analítico Jerárquico) con los datos de partidas derivados de una encuesta a los usuarios finales de la energía y a expertos. Para determinar el suministro óptimo de energía se emplearon varios métodos: la suma ponderada, el producto ponderado, las distancias de Manhattan L1, la distancia Euclidea L2 y la distancia L3. Para estas métricas se aplicaron distintos vectores de pesos para determinar las distintas estructuras de preferencias de los decisores. Finalmente, se concluyó que tener en consideración a Aceptación Social de la Energía como una función del modelo influye en el suministro de energía de cada alternativa energética. ABSTRACT Energy planning decision making is a complex task due to the multiple options to follow and objectives to meet. In order to minimize this complexity, a wide variety of methods and supporting tools have been designed. Over the last decade, rural energization has been a priority for many governments, aiming to alleviate rural to urban migration. Rural energy planning decision making must rely on financial, environmental and social costs. The purpose of this work is to define an original energy planning model named Clean and Native Energy Generation (Generación Energética Autóctona Y Limpia, GEAYL), and carry out a case study on Granma Province, Cuba. This model is based on two previous models: PAMER & SEMA. GEAYL is a multiobjective-multicriteria energy planning model, which includes five functions to be optimized: F1, to minimize financial costs; F2, to minimize CO2 emissions; F3, to minimize NOx emissions; F4, to minimize SOx emissions; and F5, to maximize energy Social Acceptability. The coefficients corresponding to the first four functions have been obtained through specialized papers and official data, and the ones belonging to F5 through an Analytic Hierarchy Process (AHP), built as per a statistical enquiry carried out on energy users and experts. F5 and the AHP application are considered to be the novelty of this model. In order to establish the optimal energy supply, several methods have been applied: weighted sum, weighted product, Manhattan distance L1, Euclidean distance L2 and L3. Several weight vectors have been applied to the mentioned distances in order to conclude the decision makers potential preference structure. Among the conclusions of this work, it must be noted that function F5, Social Acceptability, has a clear influence on every energy supply alternative.

Comparison of high-speed videokeratoscopy and ultrasound distance sensing for measuring the longitudinal corneal apex movements

Two different methods to measure binocular longitudinal corneal apex movements were synchronously applied. High-speed videokeratoscopy at a sampling frequency of 15 Hz and a customdesigned ultrasound distance sensor at 100 Hz were used for the left and the right eye, respectively. Four healthy subjects participated in the study. Simultaneously, cardiac electric cycle (ECG) was registered for each subject at 100 Hz. Each measurement took 20 s. Subjects were asked to suppress blinking during the measurements. A rigid headrest and a bite-bar were used to minimize undesirable head movements. Time, frequency and time-frequency representations of the acquired signals were obtained to establish their temporal and spectral contents. Coherence analysis was used to estimate the correlation between the measured signals. The results showed close correlation between both corneal apex movements and the cardiopulmonary system. Unraveling these relationships could lead to better understanding of interactions between ocular biomechanics and vision. The advantages and disadvantages of the two methods in the context of measuring longitudinal movements of the corneal apex are outlined.

Closing the cultural distance gap: managing value-based knowledge in MNC by using MEP

Today more than ever, generating and managing knowledge is an essential source of competitive advantage for every organization, and particularly for Multinational corporations (MNC). However, despite the undisputed agreement about the importance of creating and managing knowledge, there are still a large number of corporations that act unethically or illegally. Clearly, there is a lack of attention in gaining more knowledge about the management of ethical knowledge in organizations. This paper refers to value-based knowledge, as the process of recognise and manage those values that stand at the heart of decision-making and action in organizations. In order to support MNCs in implementing value-based knowledge process, the managerial ethical profile (MEP) has been presented as a valuable tool to facilitate knowledge management process at both the intra-organizational network level and at the inter-organizational network level.

ePortfolios and preservice teachers : governing at a distance through non-human actors

This chapter seeks to develop an analysis of the contemporary use of the ePortfolio (Electronic Portfolio) in education practices. Unlike other explorations of this new technology which are deterministic in their approach, the authors seek to reveal the techniques and practices of government which underpin the implementation of the e-portfolio. By interrogating a specific case study example from a large Australian university’s preservice teacher program, the authors find that the e-portfolio is represented as eLearning technology but serves to govern students via autonomization and self responsibilization. Using policy data and other key documents, they are able to reveal the e-portfolio as a delegated authority in the governance of preservice teachers. However, despite this ongoing trend, they suggest that like other practices of government, the e-portfolio will eventually fail. This however the authors conclude opens up space for critical thought and engagement which is not afforded presently.

Distance Education and the Integration of E-learning in a Graduate Program

Historically, distance education consisted of a combination of face-to-face blocks of time and surface mailed packages. However, advances in information technology literacy and the abundance of personal computers has placed e-learning in increased demand. The authors describe the planning, implementation, and evaluation of the blending of e-learning with face-to-face education in the postgraduate nursing forum. Experiences of this particular student group are also discussed.