Full-rate full-diversity finite feedback space-time schemes with minimum feedback and transmission duration

A Finite Feedback Scheme (FFS) for a quasi-static MIMO block fading channel with finite N-ary delay-free noise-free feedback consists of N Space-Time Block Codes (STBCs) at the transmitter, one corresponding to each possible value of feedback, and a function at the receiver that generates N-ary feedback. A number of FFSs are available in the literature that provably attain full-diversity. However, there is no known full-diversity criterion that universally applies to all FFSs. In this paper a universal necessary condition for any FFS to achieve full-diversity is given, and based on this criterion the notion of Feedback-Transmission duration optimal (FT-optimal) FFSs is introduced, which are schemes that use minimum amount of feedback N for the given transmission duration T, and minimum T for the given N to achieve full-diversity. When there is no feedback (N = 1) an FT-optimal scheme consists of a single STBC, and the proposed condition reduces to the well known necessary and sufficient condition for an STBC to achieve full-diversity. Also, a sufficient criterion for full-diversity is given for FFSs in which the component STBC yielding the largest minimum Euclidean distance is chosen, using which full-rate (N-t complex symbols per channel use) full-diversity FT-optimal schemes are constructed for all N-t > 1. These are the first full-rate full-diversity FFSs reported in the literature for T < N-t. Simulation results show that the new schemes have the best error performance among all known FFSs.

Forgotten records of Chrysopelea taprobanica Smith, 1943 (Squamata: Colubridae) from India

The colubrid snake Chrysopelea taprobanica Smith, 1943 was described from a holotype from Kanthali (= Kantalai) and paratypes from Kurunegala, both localities in Sri Lanka (formerly Ceylon) (Smith 1943). Since its description, literature pertaining to Sri Lankan snake fauna considered this taxon to be endemic to the island (Taylor 1950, Deraniyagala 1955, de Silva 1980, de Silva 1990, Somaweera 2004, Somaweera 2006, de Silva 2009, Pyron et al. 2013). In addition, earlier efforts on the Indian peninsula (e.g. Das 1994, 1997, Das 2003, Whitaker & Captain 2004, Aengals et al. 2012) and global data compilations (e.g. Wallach et al. 2014, Uetz & Hošek 2015) did not identify any record from mainland India until Guptha et al. (2015) recorded a specimen (voucher BLT 076 housed at Bio-Lab of Seshachalam Hills, Tirupathi, India) in the dry deciduous forest of Chamala, Seshachalam Biosphere Reserve in Andhra Pradesh, India in November 2013. Guptha et al. (2015) further mentioned an individual previously photographed in 2000 at Rishi Valley, Andhra Pradesh, but with no voucher specimen collected. Guptha’s record, assumed to be the first confirmed record of C. taprobanica in India, is noteworthy as it results in a large range extension, from northern Sri Lanka to eastern India with an Euclidean distance of over 400 km, as well as a change of status, i.e., species not endemic to Sri Lanka. However, at least three little-known previous records of this species from India evaded most literature and were overlooked by the researchers including ourselves.

Minimization Problems Based on Relative alpha-Entropy I: Forward Projection

Minimization problems with respect to a one-parameter family of generalized relative entropies are studied. These relative entropies, which we term relative alpha-entropies (denoted I-alpha), arise as redundancies under mismatched compression when cumulants of compressed lengths are considered instead of expected compressed lengths. These parametric relative entropies are a generalization of the usual relative entropy (Kullback-Leibler divergence). Just like relative entropy, these relative alpha-entropies behave like squared Euclidean distance and satisfy the Pythagorean property. Minimizers of these relative alpha-entropies on closed and convex sets are shown to exist. Such minimizations generalize the maximum Renyi or Tsallis entropy principle. The minimizing probability distribution (termed forward I-alpha-projection) for a linear family is shown to obey a power-law. Other results in connection with statistical inference, namely subspace transitivity and iterated projections, are also established. In a companion paper, a related minimization problem of interest in robust statistics that leads to a reverse I-alpha-projection is studied.

Avaliação dafitotoxidez de 18 espécies ocorrentes na restinga de Massambaba, Rio de Janeiro

A Área de Proteção Ambiental de Massambaba concentra diversas formações vegetais com uma grande riqueza florística e endemismos. Infelizmente esta área está sujeita à ação antrópica tanto que alguns fragmentos se encontram degradados. Para recuperar ecologicamente esta vegetação é importante compreender os mecanismos de sucessão ecológica. Como se sabe pouco sobre interações entre plantas de restinga, e menos ainda sob o prisma da alelopatia (efeito negativo que uma planta exerce em outras, ao liberar metabólitos secundários para o seu entorno),objetivou-se a realização de ensaios biológicos com espécies nativas. Inicialmente determinamos as melhores condições de extração de metabólitos, e por fim realizamos bioensaios com 18 espécies (Allagoptera aenaria, Andira legalis, Byrsonima sericea, Clusia fluminensis, Couepia ovalifolia, Erythroxylum ovalifolium, Eugenia copacabanensis, Eugenia selloi, Garcinia brasiliensis, Guapira opposita, Maytenus obtusifolia, Myrsine parvifolia, Neomitranthes obscura, Ocotea notata, Pouteria caimito, Renvoizea trinii, Tocoyena bullata e Vitex megapotamica). A aplicação dos extratos foi sobrea germinação e ocrescimento inicial de sementes de alface. Para isso, folhas destas espécies foram coletadas sazonalmente na formação arbustiva aberta não inundável (fácies alta) na restinga de Massambaba para o preparo de extratos aquosos. Os extratos foram obtidos a através da secagem das folhas à60C para posterior maceração, aquecimento, diluição e filtração, obtendo-se as concentrações de 5 e 10% de concentração (peso/volume). Os parâmetros para avaliar a fitotoxidez foram:a porcentagem ea velocidade de germinação e o comprimento da raiz após sete dias de crescimento em placas de Petri umedecidas com os extratos. Além desses três parâmetros, foi utilizado o índice de efeito global, que transforma as três variáveis em um índice único e uma analise de agrupamento (distância euclidiana, método de Ward) para classificá-las em espécies de fraca, média ou alta fitotoxidez de acordo com o valor do índice. A inibição do crescimento foi observada em todas as espécies, e verificou-se diferenças sazonais significativas, com destaque no inverno. Isso sugere que as diferenças os entre níveis de fitotoxidez estejam correlacionada são ambiente e à genética. Se a ação inibitória das espécies com maior efeito alelopático for comprovada, novas estratégias podem ser elaboradas para a reintrodução em projetos de conservação ambiental

Foraging habitats and utilization distributions of Black-necked Cranes wintering at the Napahai Wetland, China

One of the most endangered populations of Black-necked Cranes (Grus nigricollis), the central population, is declining due to habitat loss and degradation, but little is known about their space use patterns and habitat preferences. We examined the space use and habitat preferences of Black-necked Cranes during the winter of 2007-2008 at the Napahai wetland in northwest Yunnan, China, where approximately 300 Black-necked Cranes (>90% of the total central population) spent the winter. Euclidean distance analysis was employed to determine the habitat preferences of Black-necked Cranes, and a local nearest-neighbor, convex-hull construction method was used to examine space use. Our results indicate that Black-necked Cranes preferred shallow marsh and wet meadow habitats and avoided farmland and dry grassland. Core-use areas (50% isopleths) and total-use areas (100% isopleths) accounted for only 1.2% and 28.2% of the study area, respectively. We recommend that habitat protection efforts focus on shallow marsh and wet meadow habitats to maintain preferred foraging sites. Core-use areas, such as the primary foraging areas of Black-necked Cranes, should be designated as part of the core zone of the nature reserve. Monthly shifts in the core-use areas of the cranes also indicate that the reserve should be large enough to permit changes in space use. In addition to preserving habitat, government officials should also take measures to decrease human activity in areas used by foraging Black-necked Cranes.

Scale-invariant vote-based 3D recognition and registration from point clouds

This chapter presents a method for vote-based 3D shape recognition and registration, in particular using mean shift on 3D pose votes in the space of direct similarity transformations for the first time. We introduce a new distance between poses in this spacethe SRT distance. It is left-invariant, unlike Euclidean distance, and has a unique, closed-form mean, in contrast to Riemannian distance, so is fast to compute. We demonstrate improved performance over the state of the art in both recognition and registration on a (real and) challenging dataset, by comparing our distance with others in a mean shift framework, as well as with the commonly used Hough voting approach. © 2013 Springer-Verlag Berlin Heidelberg.

A face detection algorithm based on high dimensional space geometry

In this paper, a face detection algorithm which is based on high dimensional space geometry has been proposed. Then after the simulation experiment of Euclidean Distance and the introduced algorithm, it was theoretically analyzed and discussed that the proposed algorithm has apparently advantage over the Euclidean Distance. Furthermore, in our experiments in color images, the proposed algorithm even gives more surprises.

Analysis of diets of upland buzzards using stable carbon and nitrogen isotopes

We measured the stable carbon and nitrogen isotope ratios for muscles of the upland buzzards (Buteo hemilasius) and their potential food sources, plateau pikas (Ochotona curzoniae), Qinghai voles (Lasiopodomys fuscus), plateau zokors (Myospalax fontanierii), and several passerine bird species at the alpine meadow in Maduo county, Guoluo prefecture of Qinghai province, People's Republic of China, to provide diet information of upland buzzards, highlighting different diet composition of upland buzzards exposed to different locations. The results demonstrated that stable carbon isotope ratios of upland buzzards, passerine birds, plateau pikas, plateau zokors, and Qinghai voles were -24.42 +/- 0.25parts per thousand, -22.89 +/- 1.48parts per thousand, -25.30 +/- 1.47parts per thousand, -25.78 +/- 0.22parts per thousand, and -25.41 +/- 0.01parts per thousand, respectively, and stable nitrogen isotope ratios were 7.89 +/- 0.38parts per thousand, 8.37 +/- 2.05parts per thousand, 5.83 +/- 1.10parts per thousand, 5.23 +/- 0.34parts per thousand, and 8.86 +/- 0.06parts per thousand, respectively. Fractionation of stable carbon and nitrogen isotope ratios between upland buzzards and their food were 1.03parts per thousand and 2.11parts per thousand, respectively. Based on mass balance principle of stable isotopes and the Euclidean distance mixing model, upland buzzards depended mainly on plateau pikas as food (74.56%). Plateau zokors, Qinghai voles, and passerine birds only contributed a small proportion (25.44%) to diets of upland buzzards. The results were closely accordant with analyses of stomach contents and food pellets, which firmly supported the feasibility of using stable carbon and nitrogen isotope ratios to investigate diet information of upland buzzards. Another study based on stable carbon isotopes showed that upland buzzards living in the Haibei prefecture (another prefecture located in the southeast Qinghai province) mainly preyed on passerine birds (64.96% or more) as food supply. We were alarmed by the preliminary results that widespread poisoning activities of small mammals could reshape the food composition of upland buzzards, influencing the stability and sustainability of the alpine meadow. Bio-control on rodent pests should be carried out rather than the chemical measures.

基于切空间的局部嵌入映射近邻选择

针对欧式距离下局部嵌入映射近邻点选择的缺陷,从其定义出发,引入切空间距离,改进了近邻点的选择方法,从而能够更好的满足LLE对于局部线性的要求。论文用剩余方差测试其性能,通过对S-curve数据和Swiss-roll数据的仿真可以看到,基于切空间距离的方法能够更好的表示数据的输入/输出映射质量。

Activity Zones for Context-Aware Computing

Location is a primary cue in many context-aware computing systems, and is often represented as a global coordinate, room number, or Euclidean distance various landmarks. A user?s concept of location, however, is often defined in terms of regions in which common activities occur. We show how to partition a space into such regions based on patterns of observed user location and motion. These regions, which we call activity zones, represent regions of similar user activity, and can be used to trigger application actions, retrieve information based on previous context, and present information to users. We suggest that context-aware applications can benefit from a location representation learned from observing users. We describe an implementation of our system and present two example applications whose behavior is controlled by users? entry, exit, and presence in the zones.

Rozproszone algorytmy aproksymacyjne dla grafów dyskowych

Wydział Matematyki i Informatyki: Zakład Matematyki Dyskretnej

Wizualizacja kartograficzna dostępności przestrzennej w modelu monocentrycznym

Wydział Nauk Geograficznych i Geologicznych

Geometric Generalizations of the Power of Two Choices

A well-known paradigm for load balancing in distributed systems is the``power of two choices,''whereby an item is stored at the less loaded of two (or more) random alternative servers. We investigate the power of two choices in natural settings for distributed computing where items and servers reside in a geometric space and each item is associated with the server that is its nearest neighbor. This is in fact the backdrop for distributed hash tables such as Chord, where the geometric space is determined by clockwise distance on a one-dimensional ring. Theoretically, we consider the following load balancing problem. Suppose that servers are initially hashed uniformly at random to points in the space. Sequentially, each item then considers d candidate insertion points also chosen uniformly at random from the space,and selects the insertion point whose associated server has the least load. For the one-dimensional ring, and for Euclidean distance on the two-dimensional torus, we demonstrate that when n data items are hashed to n servers,the maximum load at any server is log log n / log d + O(1) with high probability. While our results match the well-known bounds in the standard setting in which each server is selected equiprobably, our applications do not have this feature, since the sizes of the nearest-neighbor regions around servers are non-uniform. Therefore, the novelty in our methods lies in developing appropriate tail bounds on the distribution of nearest-neighbor region sizes and in adapting previous arguments to this more general setting. In addition, we provide simulation results demonstrating the load balance that results as the system size scales into the millions.

Learning Embeddings for Indexing, Retrieval, and Classification, with Applications to Object and Shape Recognition in Image Databases

Nearest neighbor retrieval is the task of identifying, given a database of objects and a query object, the objects in the database that are the most similar to the query. Retrieving nearest neighbors is a necessary component of many practical applications, in fields as diverse as computer vision, pattern recognition, multimedia databases, bioinformatics, and computer networks. At the same time, finding nearest neighbors accurately and efficiently can be challenging, especially when the database contains a large number of objects, and when the underlying distance measure is computationally expensive. This thesis proposes new methods for improving the efficiency and accuracy of nearest neighbor retrieval and classification in spaces with computationally expensive distance measures. The proposed methods are domain-independent, and can be applied in arbitrary spaces, including non-Euclidean and non-metric spaces. In this thesis particular emphasis is given to computer vision applications related to object and shape recognition, where expensive non-Euclidean distance measures are often needed to achieve high accuracy. The first contribution of this thesis is the BoostMap algorithm for embedding arbitrary spaces into a vector space with a computationally efficient distance measure. Using this approach, an approximate set of nearest neighbors can be retrieved efficiently - often orders of magnitude faster than retrieval using the exact distance measure in the original space. The BoostMap algorithm has two key distinguishing features with respect to existing embedding methods. First, embedding construction explicitly maximizes the amount of nearest neighbor information preserved by the embedding. Second, embedding construction is treated as a machine learning problem, in contrast to existing methods that are based on geometric considerations. The second contribution is a method for constructing query-sensitive distance measures for the purposes of nearest neighbor retrieval and classification. In high-dimensional spaces, query-sensitive distance measures allow for automatic selection of the dimensions that are the most informative for each specific query object. It is shown theoretically and experimentally that query-sensitivity increases the modeling power of embeddings, allowing embeddings to capture a larger amount of the nearest neighbor structure of the original space. The third contribution is a method for speeding up nearest neighbor classification by combining multiple embedding-based nearest neighbor classifiers in a cascade. In a cascade, computationally efficient classifiers are used to quickly classify easy cases, and classifiers that are more computationally expensive and also more accurate are only applied to objects that are harder to classify. An interesting property of the proposed cascade method is that, under certain conditions, classification time actually decreases as the size of the database increases, a behavior that is in stark contrast to the behavior of typical nearest neighbor classification systems. The proposed methods are evaluated experimentally in several different applications: hand shape recognition, off-line character recognition, online character recognition, and efficient retrieval of time series. In all datasets, the proposed methods lead to significant improvements in accuracy and efficiency compared to existing state-of-the-art methods. In some datasets, the general-purpose methods introduced in this thesis even outperform domain-specific methods that have been custom-designed for such datasets.

An automated machine vision system for the histological grading of cervical intraepithelial neoplasia (CIN)

The histological grading of cervical intraepithelial neoplasia (CIN) remains subjective, resulting in inter- and intra-observer variation and poor reproducibility in the grading of cervical lesions. This study has attempted to develop an objective grading system using automated machine vision. The architectural features of cervical squamous epithelium are quantitatively analysed using a combination of computerized digital image processing and Delaunay triangulation analysis; 230 images digitally captured from cases previously classified by a gynaecological pathologist included normal cervical squamous epithelium (n = 30), koilocytosis (n = 46), CIN 1 (n = 52), CIN 2 (n = 56), and CIN 3 (n=46). Intra- and inter-observer variation had kappa values of 0.502 and 0.415, respectively. A machine vision system was developed in KS400 macro programming language to segment and mark the centres of all nuclei within the epithelium. By object-oriented analysis of image components, the positional information of nuclei was used to construct a Delaunay triangulation mesh. Each mesh was analysed to compute triangle dimensions including the mean triangle area, the mean triangle edge length, and the number of triangles per unit area, giving an individual quantitative profile of measurements for each case. Discriminant analysis of the geometric data revealed the significant discriminatory variables from which a classification score was derived. The scoring system distinguished between normal and CIN 3 in 98.7% of cases and between koilocytosis and CIN 1 in 76.5% of cases, but only 62.3% of the CIN cases were classified into the correct group, with the CIN 2 group showing the highest rate of misclassification. Graphical plots of triangulation data demonstrated the continuum of morphological change from normal squamous epithelium to the highest grade of CIN, with overlapping of the groups originally defined by the pathologists. This study shows that automated location of nuclei in cervical biopsies using computerized image analysis is possible. Analysis of positional information enables quantitative evaluation of architectural features in CIN using Delaunay triangulation meshes, which is effective in the objective classification of CIN. This demonstrates the future potential of automated machine vision systems in diagnostic histopathology. Copyright (C) 2000 John Wiley and Sons, Ltd.