On Root Arrangements of Polynomial-Like Functions and their Derivatives

2000 Mathematics Subject Classification: 12D10.

Noninear Integral Inequalities Involving Maxima

Снежана Христова, Кремена Стефанова, Лозанка Тренкова - В статията се изучават някои интегрални неравенства, които съдържат макси-мума на неизвестната функция на една променлива. Разглежданите неравенства са обобщения на класическото неравенство на Бихари. Значимостта на тези интегрални неравенства се дълже на широкото им приложение при качественото изследванене на различни свойства на решенията на диференциални уравнения с “максимум” и е илюстрирано с някои директни приложения.

Principles of Extremum and Application to some Problems of Analysis

AMS subject classification: 41A17, 41A50, 49Kxx, 90C25.

Monte Carlo Method for Reconstruction of Densities

2000 Mathematics Subject Classification: 65C05

Discrete Time Bisexual Branching Processes in Varying Environments

2000 Mathematics Subject Classification: 60J80

Model Mining and Efficient Verification of Software Product Lines

Software product line modeling aims at capturing a set of software products in an economic yet meaningful way. We introduce a class of variability models that capture the sharing between the software artifacts forming the products of a software product line (SPL) in a hierarchical fashion, in terms of commonalities and orthogonalities. Such models are useful when analyzing and verifying all products of an SPL, since they provide a scheme for divide-and-conquer-style decomposition of the analysis or verification problem at hand. We define an abstract class of SPLs for which variability models can be constructed that are optimal w.r.t. the chosen representation of sharing. We show how the constructed models can be fed into a previously developed algorithmic technique for compositional verification of control-flow temporal safety properties, so that the properties to be verified are iteratively decomposed into simpler ones over orthogonal parts of the SPL, and are not re-verified over the shared parts. We provide tool support for our technique, and evaluate our tool on a small but realistic SPL of cash desks.

Design of nonlinear regenerative transmission systems with high capacity

We present the design of nonlinear regenerative communication channels that have capacity above the classical Shannon capacity of the linear additive white Gaussian noise channel. The upper bound for regeneration efficiency is found and the asymptotic behavior of the capacity in the saturation regime is derived. © 2013 IEEE.

Some Coefficient Estimates for Polynomials on the Unit Interval

2000 Mathematics Subject Classification: 26C05, 26C10, 30A12, 30D15, 42A05, 42C05.

Hyperbolic Fourth-R Quadratic Equation and Holomorphic Fourth-R Polynomials

MSC 2010: 30C10, 32A30, 30G35

Implementing an agent-based model with a spatial visual display in discrete-event simulation software

There has been an increasing interest in the use of agent-based simulation and some discussion of the relative merits of this approach as compared to discrete-event simulation. There are differing views on whether an agent-based simulation offers capabilities that discrete-event cannot provide or whether all agent-based applications can at least in theory be undertaken using a discrete-event approach. This paper presents a simple agent-based NetLogo model and corresponding discrete-event versions implemented in the widely used ARENA software. The two versions of the discrete-event model presented use a traditional process flow approach normally adopted in discrete-event simulation software and also an agent-based approach to the model build. In addition a real-time spatial visual display facility is provided using a spreadsheet platform controlled by VBA code embedded within the ARENA model. Initial findings from this investigation are that discrete-event simulation can indeed be used to implement agent-based models and with suitable integration elements such as VBA provide the spatial displays associated with agent-based software.

Method for computing the optimal signal distribution and channel capacity

An iterative method for computing the channel capacity of both discrete and continuous input, continuous output channels is proposed. The efficiency of new method is demonstrated in comparison with the classical Blahut - Arimoto algorithm for several known channels. Moreover, we also present a hybrid method combining advantages of both the Blahut - Arimoto algorithm and our iterative approach. The new method is especially efficient for the channels with a priory unknown discrete input alphabet.

Stability of Ampelometric Characteristics of Vitis vinifera L. cv. 'Syrah' and 'Sauvignon blanc' Leaves: Impact of Within-vineyard Variability and Pruning Method/Bud Load

Historically, grapevine (Vitis vinifera L.) leaf characterisation has been a driving force in the identification of cultivars. In this study, ampelometric (foliometric) analysis was done on leaf samples collected from hand-pruned, mechanically pruned and minimally pruned ‘Sauvignon blanc’ and ‘Syrah’ vines to estimate the impact of within-vineyard variability and a change in bud load on the stability of leaf properties. The results showed that within-vineyard variability of ampelometric characteristics was high within a cultivar, irrespective of bud load. In terms of the O.I.V. coding system, zero to four class differences were observed between minimum and maximum values of each characteristic. The value of variability of each characteristic was different between the three levels of bud load and the two cultivars. With respect to bud load, the number of shoots per vine had a significant effect on the characteristics of the leaf laminae. Single leaf area and lengths of veins changed significantly for both cultivars, irrespective of treatment, while angle between veins proved to be a stable characteristic. A large number of biometric data can be recorded on a single leaf; the data measured on several leaves, however, are not necessarily unique for a specific cultivar. The leaf characteristics analysed in this study can be divided into two groups according to the response to a change in bud load, i.e. stable (angles between the veins, depths of sinuses) and variable (length of the veins, length of the petiole, single leaf area). The variable characteristics are not recommended to be used in cultivar identification, unless the pruning method/bud load is known.

A longitudinal study of Project Trio: A dropout prevention program in a large urban environment

The subject of dropout prevention/reduction is deservedly receiving attention as a problem that, if not resolved, could threaten our national future.^ This study investigates a small segment of the overall dropout problem, which has apparently unique features of program design and population selection. The evidence presented here should add to the knowledge bank of this complicated problem.^ Project Trio was one of a number of dropout prevention programs and activities which were conducted in Dade County school years 1984-85 and 1985-86, and it is here investigated longitudinally through the end of the 1987-88 school year. It involved 17 junior and senior high schools, and 27 programs, 10 the first year and 17 the second, with over 1,000 total students, who had been selected by the schools from a list of the "at risk" students provided by the district, and were divided approximately evenly into the classical research design of an experimental group and the control group, which following standard procedure was to take the regular school curriculum. No school had more than 25 students in either group.^ Each school modified the basic design of the project to accommodate the individual school characteristics and the perceived needs of their students; however all schools projects were to include some form of academic enhancement, counseling and career awareness study.^ The conclusion of this study was that the control group had a significantly lower dropout rate than the experimental group. Though impossible to make a certain determination of the reasons for this unexpected result, it appears from evidence presented that one cause may have been inadequate administration at the local level.^ This study was also a longitudinal investigation of the "at risk" population as a whole for the three and four year period, to determine if academic factors were present in records may be used to identify dropout proneness.^ A significant correlation was found between dropping out and various measures including scores on the Quality of School Life Instrument, attendance, grade point averages, mathematics grades, and overage in grade, important identifiers in selection for dropout prevention programs. ^

A reliability centered maintenance decision system for a discrete part manufacturing facility

This thesis develops and validates the framework of a specialized maintenance decision support system for a discrete part manufacturing facility. Its construction utilizes a modular approach based on the fundamental philosophy of Reliability Centered Maintenance (RCM). The proposed architecture uniquely integrates System Decomposition, System Evaluation, Failure Analysis, Logic Tree Analysis, and Maintenance Planning modules. It presents an ideal solution to the unique maintenance inadequacies of modern discrete part manufacturing systems. Well established techniques are incorporated as building blocks of the system's modules. These include Failure Mode Effect and Criticality Analysis (FMECA), Logic Tree Analysis (LTA), Theory of Constraints (TOC), and an Expert System (ES). A Maintenance Information System (MIS) performs the system's support functions. Validation was performed by field testing of the system at a Miami based manufacturing facility. Such a maintenance support system potentially reduces downtime losses and contributes to higher product quality output. Ultimately improved profitability is the final outcome. ^

Statistical analysis and meta-analysis of microarray data

The microarray technology provides a high-throughput technique to study gene expression. Microarrays can help us diagnose different types of cancers, understand biological processes, assess host responses to drugs and pathogens, find markers for specific diseases, and much more. Microarray experiments generate large amounts of data. Thus, effective data processing and analysis are critical for making reliable inferences from the data. ^ The first part of dissertation addresses the problem of finding an optimal set of genes (biomarkers) to classify a set of samples as diseased or normal. Three statistical gene selection methods (GS, GS-NR, and GS-PCA) were developed to identify a set of genes that best differentiate between samples. A comparative study on different classification tools was performed and the best combinations of gene selection and classifiers for multi-class cancer classification were identified. For most of the benchmarking cancer data sets, the gene selection method proposed in this dissertation, GS, outperformed other gene selection methods. The classifiers based on Random Forests, neural network ensembles, and K-nearest neighbor (KNN) showed consistently god performance. A striking commonality among these classifiers is that they all use a committee-based approach, suggesting that ensemble classification methods are superior. ^ The same biological problem may be studied at different research labs and/or performed using different lab protocols or samples. In such situations, it is important to combine results from these efforts. The second part of the dissertation addresses the problem of pooling the results from different independent experiments to obtain improved results. Four statistical pooling techniques (Fisher inverse chi-square method, Logit method. Stouffer's Z transform method, and Liptak-Stouffer weighted Z-method) were investigated in this dissertation. These pooling techniques were applied to the problem of identifying cell cycle-regulated genes in two different yeast species. As a result, improved sets of cell cycle-regulated genes were identified. The last part of dissertation explores the effectiveness of wavelet data transforms for the task of clustering. Discrete wavelet transforms, with an appropriate choice of wavelet bases, were shown to be effective in producing clusters that were biologically more meaningful. ^