Evaluation of operational SSM/I ice-concentration algorithms

The United States National Ice Center (NIC) provides weekly ice analyses of the Arctic and Antarctic using information from ice reconnaissance, ship reports and high-resolution satellite imagery. In cloud-covered areas and regions lacking imagery, the higher-resolution sources are augmented by ice concentrations derived from Defense Meteorological Satellite Program (DMSP) Special Sensor Microwave/Imager (SSMII) passive-microwave imagery. However, the SSMII-derived ice concentrations are limited by low resolution and uncertainties in thin-ice regions. Ongoing research at NIC is attempting to improve the utility of these SSMII products for operational sea-ice analyses. The refinements of operational algorithms may also aid future scientific studies. Here we discuss an evaluation of the standard operational ice-concentration algorithm, Cal/Val, with a possible alternative, a modified NASA Team algorithm. The modified algorithm compares favorably with CallVal and is a substantial improvement over the standard NASA Team algorithm in thin-ice regions that are of particular interest to operational activities.

Dynamic Traffic Grooming Algorithms for Reconfigurable SONET Over WDM Networks

The emergence of wavelength-division multiplexing (WDM) technology provides the capability for increasing the bandwidth of synchronous optical network (SONET) rings by grooming low-speed traffic streams onto different high-speed wavelength channels. Since the cost of SONET add–drop multiplexers (SADM) at each node dominates the total cost of these networks, how to assign the wavelength, groom the traffic, and bypass the traffic through the intermediate nodes has received a lot of attention from researchers recently. Moreover, the traffic pattern of the optical network changes from time to time. How to develop dynamic reconfiguration algorithms for traffic grooming is an important issue. In this paper, two cases (best fit and full fit) for handling reconfigurable SONET over WDM networks are proposed. For each approach, an integer linear programming model and heuristic algorithms (TS-1 and TS-2, based on the tabu search method) are given. The results demonstrate that the TS-1 algorithm can yield better solutions but has a greater running time than the greedy algorithm for the best fit case. For the full fit case, the tabu search heuristic yields competitive results compared with an earlier simulated annealing based method and it is more stable for the dynamic case.

Routing Algorithms for All-Optical Networks with Power Considerations: The Unicast Case

In this paper, we investigate the problem of routing connections in all-optical networks while allowing for degradation of routed signals by different optical components. To overcome the complexity of the problem, we divide it into two parts. First, we solve the pure RWA problem using fixed routes for every connection. Second, power assignment is accomplished by either using the smallest-gain first (SGF) heuristic or using a genetic algorithm. Numerical examples on a wide variety of networks show that (a) the number of connections established without considering the signal attenuation was most of the time greater than that achievable considering attenuation and (b) the genetic solution quality was much better than that of SGF, especially when the conflict graph of the connections generated by the linear solver is denser.

Approximation Algorithms for Survivable Multicommodity Flow Problems with Applications to Network Design

Multicommodity flow (MF) problems have a wide variety of applications in areas such as VLSI circuit design, network design, etc., and are therefore very well studied. The fractional MF problems are polynomial time solvable while integer versions are NP-complete. However, exact algorithms to solve the fractional MF problems have high computational complexity. Therefore approximation algorithms to solve the fractional MF problems have been explored in the literature to reduce their computational complexity. Using these approximation algorithms and the randomized rounding technique, polynomial time approximation algorithms have been explored in the literature. In the design of high-speed networks, such as optical wavelength division multiplexing (WDM) networks, providing survivability carries great significance. Survivability is the ability of the network to recover from failures. It further increases the complexity of network design and presents network designers with more formidable challenges. In this work we formulate the survivable versions of the MF problems. We build approximation algorithms for the survivable multicommodity flow (SMF) problems based on the framework of the approximation algorithms for the MF problems presented in [1] and [2]. We discuss applications of the SMF problems to solve survivable routing in capacitated networks.

Dynamic traffic grooming algorithms for reconfigurable SONET over WDM networks

The emergence of Wavelength Division Multiplexing (WDM) technology provides the capability for increasing the bandwidth of Synchronous Optical Network (SONET) rings by grooming low-speed traffic streams onto different high-speed wavelength channels. Since the cost of SONET add-drop multiplexers (SADM) at each node dominates the total cost of these networks, how to assign the wavelength, groom in the traffic and bypass the traffic through the intermediate nodes has received a lot of attention from researchers recently.

Bandit-Based Algorithms for Budgeted Learning

We explore the problem of budgeted machine learning, in which the learning algorithm has free access to the training examples’ labels but has to pay for each attribute that is specified. This learning model is appropriate in many areas, including medical applications. We present new algorithms for choosing which attributes to purchase of which examples in the budgeted learning model based on algorithms for the multi-armed bandit problem. All of our approaches outperformed the current state of the art. Furthermore, we present a new means for selecting an example to purchase after the attribute is selected, instead of selecting an example uniformly at random, which is typically done. Our new example selection method improved performance of all the algorithms we tested, both ours and those in the literature.

Distribution of Dioecious Eastern Red Cedar (Juniperus virginiana) along an Environmental Gradient in Ogallala, NE.

Abstract The purpose of this research was to study the sex distribution and energy allocation of dioecious Eastern Red Cedars (Juniperus virginiana) along an environmental resource gradient. The trees surveyed were growing in a canyon located at the University of Nebraska’s Cedar Point Biological Research Station in Ogallala, Nebraska. Due to the geography of this canyon, environmental factors necessary for plant growth should vary depending on the tree’s location within the canyon. These factors include water availability, sun exposure, ground slope, and soil nitrogen content, all of which are necessary for carbon acquisition. Juniperus virginiana is a dioecious conifer. Dioecious plants maintain male and female reproductive structures on separate individuals. Therefore, proximal spatial location is essential for pollination and successful reproduction. Typically female reproductive structures are more costly and require a greater investment of carbon and nitrogen. For this reason, growth, survival and successful reproduction are more likely to be limited by environmental resources for females than for male individuals. If this is true for Juniperus virginiana, females should be located in more nutrient and water rich areas than males. This also assumes that females can not be reproductively successful in areas of poor environmental quality. Therefore, reproductive males should be more likely to inhabit environments with relatively lower resource availability than females. Whether the environment affects sexual determination or just limits survival of different sexes is still relatively unknown. In order to view distribution trends along the environmental gradient, the position of the tree in the canyon transect was compared to its sex. Any trend in sex should correspond with varying environmental factors in the canyon, ie: sunlight availability, aspect, and ground slope. The individuals’ allocation to growth and reproduction was quantified first by comparing trunk diameter at six inches above ground to sex and location of the tree. The feature of energy allocation was further substantiated by comparing carbon and nitrogen content in tree leaf tissue and soil to location and sex of each individual. Carbon and nitrogen in soil indicate essential nutrient availability to the individual, while C and N in leaf tissue indicate nutrient limitation experienced by the tree. At the conclusion of this experiment, there is modest support that survival and fecundity of females demands environments relatively richer in nutrients, than needed by males to survive and be reproductively active. Side of the canyon appeared to have an influence on diameter of trees, frequency of sex and carbon and nitrogen leaf content. While this information indicated possible trends in the relation of sex to nutrient availability, most of the environmental variables presumed responsible for the sex distribution bias differed minutely and may not have been biologically significant to tree growth.

Influence of a narrow depth gradient and season on the morphology, phenology, and epibiosis of the brown alga Sargassum cymosum

Temporal and spatial fluctuations of environmental parameters are normally assigned as causes of variations in morpho-phenological characters of seaweeds and in their epibionts, but formal tests of such hypotheses are lacking, especially in narrow gradients. The present study evaluated the influence of a very small depth gradient (1 to 3 m) and of subtle seasonality characteristic of tropical areas on morpho-phenological traits and on the occurrence of sessile epiphytic organisms using a controlled orthogonal sampling design in a sublittoral population of the tropical brown alga Sargassum cymosum. Four temporal samples were obtained over a one-year period at three depths using nine replicates. The wet weight, maximum length, number of primary and secondary branches, and proportion of secondary branches with receptacles were recorded. Epibiosis was estimated by visual evaluation of percentage cover on secondary branches. Algal morphology varied as a function of the period of the year (weaker effect) and depth (stronger effect) but in different ways for each variable analysed. In general, fronds tended to be shorter, heavier, and more ramified in shallower areas. In relation to time, the morphological characters tended mostly to present higher values in January (summer) and/or April (autumn). Frequency of receptacles did not depend on algal morphology and depth at all but varied in time, although only in the deepest area. Epibiosis also did not depend on algal morphology but varied in relation to time (stronger effect) and, to a lesser extent, depth (weaker effect). The effect of time upon epibiosis also depended on the biological group analysed. These data support the hypothesis that algal morphology varies in relation to period of the year and depth, even under small temporal and spatial environmenal gradients.

Efficient Forest Data Structure for Evolutionary Algorithms Applied to Network Design

The design of a network is a solution to several engineering and science problems. Several network design problems are known to be NP-hard, and population-based metaheuristics like evolutionary algorithms (EAs) have been largely investigated for such problems. Such optimization methods simultaneously generate a large number of potential solutions to investigate the search space in breadth and, consequently, to avoid local optima. Obtaining a potential solution usually involves the construction and maintenance of several spanning trees, or more generally, spanning forests. To efficiently explore the search space, special data structures have been developed to provide operations that manipulate a set of spanning trees (population). For a tree with n nodes, the most efficient data structures available in the literature require time O(n) to generate a new spanning tree that modifies an existing one and to store the new solution. We propose a new data structure, called node-depth-degree representation (NDDR), and we demonstrate that using this encoding, generating a new spanning forest requires average time O(root n). Experiments with an EA based on NDDR applied to large-scale instances of the degree-constrained minimum spanning tree problem have shown that the implementation adds small constants and lower order terms to the theoretical bound.

Variation in liana abundance and biomass along an elevational gradient in the tropical Atlantic Forest (Brazil)

Lianas play a key role in forest structure, species diversity, as well as functional aspects of tropical forests. Although the study of lianas in the tropics has increased dramatically in recent years, basic information on liana communities for the Brazilian Atlantic Forest is still scarce. To understand general patterns of liana abundance and biomass along an elevational gradient (0-1,100 m asl) of coastal Atlantic Forest, we carried out a standard census for lianas a parts per thousand yen1 cm in five 1-ha plots distributed across different forest sites. On average, we found a twofold variation in liana abundance and biomass between lowland and other forest types. Large lianas (a parts per thousand yen10 cm) accounted for 26-35% of total liana biomass at lower elevations, but they were not recorded in montane forests. Although the abundance of lianas displayed strong spatial structure at short distances, the present local forest structure played a minor role structuring liana communities at the scale of 0.01 ha. Compared to similar moist and wet Neotropical forests, lianas are slightly less abundant in the Atlantic Forest, but the total biomass is similar. Our study highlights two important points: (1) despite some studies have shown the importance of small-scale canopy disturbance and support availability, the spatial scale of the relationships between lianas and forest structure can vary greatly among tropical forests; (2) our results add to the evidence that past canopy disturbance levels and minimum temperature variation exert influence on the structure of liana communities in tropical moist forests, particularly along short and steep elevational gradients.

Collaborative fuzzy clustering algorithms: some refinements and design guidelines

There are some variants of the widely used Fuzzy C-Means (FCM) algorithm that support clustering data distributed across different sites. Those methods have been studied under different names, like collaborative and parallel fuzzy clustering. In this study, we offer some augmentation of the two FCM-based clustering algorithms used to cluster distributed data by arriving at some constructive ways of determining essential parameters of the algorithms (including the number of clusters) and forming a set of systematically structured guidelines such as a selection of the specific algorithm depending on the nature of the data environment and the assumptions being made about the number of clusters. A thorough complexity analysis, including space, time, and communication aspects, is reported. A series of detailed numeric experiments is used to illustrate the main ideas discussed in the study.

A note on the local power of the LR, Wald, score and gradient tests

This paper examines the local power of the likelihood ratio, Wald, score and gradient tests under the presence of a scalar parameter, phi say, that is orthogonal to the remaining parameters. We show that some of the coefficients that define the local powers remain unchanged regardless of whether phi is known or needs to be estimated, where as the others can be written as the sum of two terms, the first of which being the corresponding term obtained as if phi were known, and the second, an additional term yielded by the fact that phi is unknown. The contribution of each set of parameters on the local powers of the tests can then be examined. Various implications of our main result are stated and discussed. Several examples are presented for illustrative purposes

alpha-6 Integrin Expression in Bovine Spermatogonial Cells Purified by Discontinuous Percoll Density Gradient

The study of spermatogonial stem cells (SSCs) provides a model to better understand adult stem cell biology. Besides the biomedical potential to perform studies of infertility in many species, SSCs hold a promising application at animal transgenesis. Because stem cells are thought to be associated with basement membranes, expression of alpha-6 integrin has been investigated as a marker of type A spermatogonial cells, which are considered SSCs because of their undifferentiated status and self-renewal ability. In this manner, the aim of this study was to isolate type A SSCs from adult bulls by a two-step enzymatic procedure followed by a discontinuous Percoll density gradient purification and verify the expression of alpha-6 integrin by flow cytometry and real-time RT-PCR before and after Percoll purification. Spermatogonial cells were successfully obtained using the two-step enzymatic digestion. An average of 1 x 10(5) viable cells per gram of testis was isolated. However, the discontinuous Percoll did not purify isolated cells regarding alpha-6 integrin expression. Flow cytometry analysis demonstrated no differences in the alpha-6 integrin expression between cell samples before and after Percoll purification (p = 0.5636). The same was observed in the real-time PCR analysis (p > 0.05). In addition to alpha-6 integrin, the expression of GFR alpha-1 and PGP9.5, known bovine SSCs markers, was detected in all samples studied. Considering that Percoll can reduce cell viability, it is possible to conclude that Percoll density gradient is not suitable to purify bovine SSC, according to alpha-6 integrin expression.

Continuity of Lyapunov functions and of energy level for generalized gradient semigroup

The global attractor of a gradient-like semigroup has a Morse decomposition. Associated to this Morse decomposition there is a Lyapunov function (differentiable along solutions)-defined on the whole phase space- which proves relevant information on the structure of the attractor. In this paper we prove the continuity of these Lyapunov functions under perturbation. On the other hand, the attractor of a gradient-like semigroup also has an energy level decomposition which is again a Morse decomposition but with a total order between any two components. We claim that, from a dynamical point of view, this is the optimal decomposition of a global attractor; that is, if we start from the finest Morse decomposition, the energy level decomposition is the coarsest Morse decomposition that still produces a Lyapunov function which gives the same information about the structure of the attractor. We also establish sufficient conditions which ensure the stability of this kind of decomposition under perturbation. In particular, if connections between different isolated invariant sets inside the attractor remain under perturbation, we show the continuity of the energy level Morse decomposition. The class of Morse-Smale systems illustrates our results.

A survey of evolutionary algorithms for decision-tree induction

This paper presents a survey of evolutionary algorithms that are designed for decision-tree induction. In this context, most of the paper focuses on approaches that evolve decision trees as an alternate heuristics to the traditional top-down divide-and-conquer approach. Additionally, we present some alternative methods that make use of evolutionary algorithms to improve particular components of decision-tree classifiers. The paper's original contributions are the following. First, it provides an up-to-date overview that is fully focused on evolutionary algorithms and decision trees and does not concentrate on any specific evolutionary approach. Second, it provides a taxonomy, which addresses works that evolve decision trees and works that design decision-tree components by the use of evolutionary algorithms. Finally, a number of references are provided that describe applications of evolutionary algorithms for decision-tree induction in different domains. At the end of this paper, we address some important issues and open questions that can be the subject of future research.