Decomposability problem on branched coverings

Given a branched covering of degree d between closed surfaces, it determines a collection of partitions of d, the branch data. In this work we show that any branch data are realized by an indecomposable primitive branched covering on a connected closed surface N with chi(N) <= 0. This shows that decomposable and indecomposable realizations may coexist. Moreover, we characterize the branch data of a decomposable primitive branched covering. Bibliography: 20 titles.

Cultural understanding: rethinking music teacher education in a multicultural Australia

This paper provides a multicultural perspective to music education in Australia and makes recommendations for the creation of more suitable intercultural training programs in Australian universities. It explores issues of multiculturalism in higher education institutions and argues that music education is a useful platform to address and rethink cultural diversity, where difference can be celebrated. Within Australian multicultural society, the rights and traditions of all people are recognized, respected and included. In this process, higher education institutions are challenged to prepare student teachers to meet the needs of society. This involves cultural understanding and the creation of multicultural curricula. From reflecting on current music education programs offered at Deakin University, Melbourne, it is argued that there is need to rethink current approaches to music education pedagogy. Although there are attempts to have an all inclusive approach in teacher training, the music curriculum is still trapped in the potpourri effect of trying to create culturally responsive teachers for every permutation of the multicultural classroom. When Australian society, ideally approaches true styles of multicultural music, teachers and students will celebrate the rich diversity of this nation.

Blind identification of FIR MIMO channels by decorrelating subchannels

We study blind identification and equalization of finite impulse response (FIR) and multi-input and multi-output (MIMO) channels driven by colored signals. We first show a sufficient condition for an FIR MIMO channel to be identifiable up to a scaling and permutation using the second-order statistics of the channel output. This condition is that the channel matrix is irreducible (but not necessarily column-reduced), and the input signals are mutually uncorrelated and of distinct power spectra. We also show that this condition is necessary in the sense that no single part of the condition can be further weakened without another part being strengthened. While the above condition is a strong result that sets a fundamental limit of blind identification, there does not yet exist a working algorithm under that condition. In the second part of this paper, we show that a method called blind identification via decorrelating subchannels (BIDS) can uniquely identify an FIR MIMO channel if a) the channel matrix is nonsingular (almost everywhere) and column-wise coprime and b) the input signals are mutually uncorrelated and of sufficiently diverse power spectra. The BIDS method requires a weaker condition on the channel matrix than that required by most existing methods for the same problem.

Induced ordered weighted averaging operators

Since the introduction of the ordered weighted averaging operator [18], the OWA has received great attention with applications in fields including decision making, recommender systems [8, 21], classification [10] and data mining [16] among others. The most important step in the calculation of the OWA is the permutation of the input vector according to the size of its arguments. In some applications, it makes sense that the inputs be reordered by values different to those used in calculation. For instance, if we have a number of mobile sensor readings, we may wish to allocate more importance to the reading taken from the sensor closest to us at a given point in time, rather than the largest reading.

Strong population genetic structure and its management implications in the mud carp Cirrhinus molitorella, an indigenous freshwater species subject to an aquaculture and culture-based fishery

This study investigated population genetic structure and diversity of mud carp Cirrhinus molitorella, a species widely used in aquaculture and culture-based fisheries in China and Mekong River riparian countries. Seven newly developed and one published microsatellite DNA markers were used to analyse samples from six wild locations, four hatchery broodstocks and one farmed site from the Mekong, Red and Pearl Rivers. Significant genetic structure was detected in C. molitorella, with isolation-by-distance being a strong force in the Mekong. Pair-wise F_ST, Fisher's exact tests for population differentiation, permutation tests and individual-based structure analysis all support the recognition of a sample originating from Toul Krasaing Lake (Cambodia) and one between Kratie and Stung Treng (Cambodia) as distinct from the remainder of the sampled range. Samples from the main upper Mekong and the Nam Khan River were significantly differentiated, but on a time scale inferred to be short (i.e. by genetic drift, not sufficient for evolution of new microsatellite alleles). The Mekong stock of C. molitorella was strongly differentiated from those from the Red and Pearl Rivers, inferred to be on an evolutionary time scale. Finer-scale sampling is warranted to further improve the understanding of genetic interactions among fish from the Mekong and its tributaries. Detailed studies on the ecology of C. molitorella (e.g. migration pathways and preferred spawning habitats) would provide useful information to explain the patterns of genetic structure detected here, and deepen insights about evolutionary distinctiveness of the population units.

Guest editorial : In Journal of networks, v.7 n.3

Networking of computing devices has been going through rapid evolution and thus continuing to be an ever expanding area of importance in recent years. New technologies, protocols, services and usage patterns have contributed to the major research interests in this area of computer science. The current special issue is an effort to bring forward some of these interesting developments that are being pursued by researchers at present in different parts of the globe. Our objective is to provide the readership with some insight into the latest innovations in computer networking through this. This Special Issue presents selected papers from the thirteenth conference of the series (ICCIT 2010) held during December 23-25, 2010 at the Ahsanullah University of Science and Technology. The first ICCIT was held in Dhaka, Bangladesh, in 1998. Since then the conference has grown to be one of the largest computer and IT related research conferences in the South Asian region, with participation of academics and researchers from many countries around the world. Starting in 2008 the proceedings of ICCIT are included in IEEExplore. In 2010, a total of 410 full papers were submitted to the conference of which 136 were accepted after reviews conducted by an international program committee comprising 81 members from 16 countries. This was tantamount to an acceptance rate of 33%. From these 136 papers, 14 highly ranked manuscripts were invited for this Special Issue. The authors were advised to enhance their papers significantly and submit them to undergo review for suitability of inclusion into this publication. Of those, eight papers survived the review process and have been selected for inclusion in this Special Issue. The authors of these papers represent academic and/or research institutions from Australia, Bangladesh, Japan, Korea and USA. These papers address issues concerning different domains of networks namely, optical fiber communication, wireless and interconnection networks, issues related to networking hardware and software and network mobility. The paper titled “Virtualization in Wireless Sensor Network: Challenges and Opportunities” argues in favor of bringing in different heterogeneous sensors under a common virtual framework so that the issues like flexibility, diversity, management and security can be handled practically. The authors Md. Motaharul Islam and Eui-Num Huh propose an architecture for sensor virtualization. They also present the current status and the challenges and opportunities for further research on the topic. The manuscript “Effect of Polarization Mode Dispersion on the BER Performance of Optical CDMA” deals with impact of polarization mode dispersion on the bit error rate performance of direct sequence optical code division multiple access. The authors, Md. Jahedul Islam and Md. Rafiqul Islam present an analytical approach toward determining the impact of different performance parameters. The authors show that the bit error rate performance improves significantly by the third order polarization mode dispersion than its first or second order counterparts. The authors Md. Shohrab Hossain, Mohammed Atiquzzaman and William Ivancic of the paper “Cost and Efficiency Analysis of NEMO Protocol Entities” present an analytical model for estimating the cost incurred by major mobility entities of a NEMO. The authors define a new metric for cost calculation in the process. Both the newly developed metric and the analytical model are likely to be useful to network engineers in estimating the resource requirement at the key entities while designing such a network. The article titled “A Highly Flexible LDPC Decoder using Hierarchical Quasi-Cyclic Matrix with Layered Permutation” deals with Low Density Parity Check decoders. The authors, Vikram Arkalgud Chandrasetty and Syed Mahfuzul Aziz propose a novel multi-level structured hierarchical matrix approach for generating codes of different lengths flexibly depending upon the requirement of the application. The manuscript “Analysis of Performance Limitations in Fiber Bragg Grating Based Optical Add-Drop Multiplexer due to Crosstalk” has been contributed by M. Mahiuddin and M. S. Islam. The paper proposes a new method of handling crosstalk with a fiber Bragg grating based optical add drop multiplexer (OADM). The authors show with an analytical model that different parameters improve using their proposed OADM. The paper “High Performance Hierarchical Torus Network Under Adverse Traffic Patterns” addresses issues related to hierarchical torus network (HTN) under adverse traffic patterns. The authors, M.M. Hafizur Rahman, Yukinori Sato, and Yasushi Inoguchi observe that dynamic communication performance of an HTN under adverse traffic conditions has not yet been addressed. The authors evaluate the performance of HTN for comparison with some other relevant networks. It is interesting to see that HTN outperforms these counterparts in terms of throughput and data transfer under adverse traffic. The manuscript titled “Dynamic Communication Performance Enhancement in Hierarchical Torus Network by Selection Algorithm” has been contributed by M.M. Hafizur Rahman, Yukinori Sato, and Yasushi Inoguchi. The authors introduce three simple adapting routing algorithms for efficient use of physical links and virtual channels in hierarchical torus network. The authors show that their approaches yield better performance for such networks. The final title “An Optimization Technique for Improved VoIP Performance over Wireless LAN” has been contributed by five authors, namely, Tamal Chakraborty, Atri Mukhopadhyay, Suman Bhunia, Iti Saha Misra and Salil K. Sanyal. The authors propose an optimization technique for configuring the parameters of the access points. In addition, they come up with an optimization mechanism in order to tune the threshold of active queue management system appropriately. Put together, the mechanisms improve the VoIP performance significantly under congestion. Finally, the Guest Editors would like to express their sincere gratitude to the 15 reviewers besides the guest editors themselves (Khalid M. Awan, Mukaddim Pathan, Ben Townsend, Morshed Chowdhury, Iftekhar Ahmad, Gour Karmakar, Shivali Goel, Hairulnizam Mahdin, Abdullah A Yusuf, Kashif Sattar, A.K.M. Azad, F. Rahman, Bahman Javadi, Abdelrahman Desoky, Lenin Mehedy) from several countries (Australia, Bangladesh, Japan, Pakistan, UK and USA) who have given immensely to this process. They have responded to the Guest Editors in the shortest possible time and dedicated their valuable time to ensure that the Special Issue contains high-quality papers with significant novelty and contributions.

Identification of concurrent control chart patterns with singular spectrum analysis and learning vector quantization

Identification of unnatural control chart patterns (CCPs) from manufacturing process measurements is a critical task in quality control as these patterns indicate that the manufacturing process is out-of-control. Recently, there have been numerous efforts in developing pattern recognition and classification methods based on artificial neural network to automatically recognize unnatural patterns. Most of them assume that a single type of unnatural pattern exists in process data. Due to this restrictive assumption, severe performance degradations are observed in these methods when unnatural concurrent CCPs present in process data. To address this problem, this paper proposes a novel approach based on singular spectrum analysis (SSA) and learning vector quantization network to identify concurrent CCPs. The main advantage of the proposed method is that it can be applied to the identification of concurrent CCPs in univariate manufacturing processes. Moreover, there are no permutation and scaling ambiguities in the CCPs recovered by the SSA. These desirable features make the proposed algorithm an attractive alternative for the identification of concurrent CCPs. Computer simulations and a real application for aluminium smelting processes confirm the superior performance of proposed algorithm for sets of typical concurrent CCPs.

Propensity score matching and variations on the balancing test

Balancing tests are diagnostics designed for use with propensity score methods, a widely used non-experimental approach in the evaluation literature. Such tests provide useful information on whether plausible counterfactuals have been created. Currently, multiple balancing tests exist in the literature but it is unclear which is the most useful. This article highlights the poor size properties of commonly employed balancing tests and attempts to shed some light on the link between the results of balancing tests and bias of the evaluation estimator. The simulation results suggest that in scenarios where the conditional independence assumption holds, a permutation version of the balancing test described in Dehejia and Wahba (Rev Econ Stat 84:151–161, 2002) can be useful in applied study. The proposed test has good size properties. In addition, the test appears to have good power for detecting a misspecification in the link function and some power for detecting an omission of relevant non-linear terms involving variables that are included at a lower order.

Nonnegative Matrix Factorization Applied to Nonlinear Speech and Image Cryptosystems

Nonnegative matrix factorization (NMF) is widely used in signal separation and image compression. Motivated by its successful applications, we propose a new cryptosystem based on NMF, where the nonlinear mixing (NLM) model with a strong noise is introduced for encryption and NMF is used for decryption. The security of the cryptosystem relies on following two facts: 1) the constructed multivariable nonlinear function is not invertible; 2) the process of NMF is unilateral, if the inverse matrix of the constructed linear mixing matrix is not nonnegative. Comparing with Lin's method (2006) that is a theoretical scheme using one-time padding in the cryptosystem, our cipher can be used repeatedly for the practical request, i.e., multitme padding is used in our cryptosystem. Also, there is no restriction on statistical characteristics of the ciphers and the plaintexts. Thus, more signals can be processed (successfully encrypted and decrypted), no matter they are correlative, sparse, or Gaussian. Furthermore, instead of the number of zero-crossing-based method that is often unstable in encryption and decryption, an improved method based on the kurtosis of the signals is introduced to solve permutation ambiguities in waveform reconstruction. Simulations are given to illustrate security and availability of our cryptosystem.

Fifteen to twenty percent of HIV substitution mutations are associated with recombination

HIV undergoes high rates of mutation and recombination during reverse transcription, but it is not known whether these events occur independently or are linked mechanistically. Here we used a system of silent marker mutations in HIV and a single round of infection in primary T lymphocytes combined with a high-throughput sequencing and mathematical modeling approach to directly estimate the viral recombination and mutation rates. From >7 million nucleotides (nt) of sequences from HIV infection, we observed 4,801 recombination events and 859 substitution mutations (≈1.51 and 0.12 events per 1,000 nt, respectively). We used experimental controls to account for PCR-induced and transfection-induced recombination and sequencing error. We found that the single-cycle virus-induced mutation rate is 4.6 × 10(-5) mutations per nt after correction. By sorting of our data into recombined and nonrecombined sequences, we found a significantly higher mutation rate in recombined regions (P = 0.003 by Fisher's exact test). We used a permutation approach to eliminate a number of potential confounding factors and confirm that mutation occurs around the site of recombination and is not simply colocated in the genome. By comparing mutation rates in recombined and nonrecombined regions, we found that recombination-associated mutations account for 15 to 20% of all mutations occurring during reverse transcription.

PPFSCADA: Privacy preserving framework for SCADA data publishing

Supervisory Control and Data Acquisition (SCADA) systems control and monitor industrial and critical infrastructure functions, such as electricity, gas, water, waste, railway, and traffic. Recent attacks on SCADA systems highlight the need for stronger SCADA security. Thus, sharing SCADA traffic data has become a vital requirement in SCADA systems to analyze security risks and develop appropriate security solutions. However, inappropriate sharing and usage of SCADA data could threaten the privacy of companies and prevent sharing of data. In this paper, we present a privacy preserving strategy-based permutation technique called PPFSCADA framework, in which data privacy, statistical properties and data mining utilities can be controlled at the same time. In particular, our proposed approach involves: (i) vertically partitioning the original data set to improve the performance of perturbation; (ii) developing a framework to deal with various types of network traffic data including numerical, categorical and hierarchical attributes; (iii) grouping the portioned sets into a number of clusters based on the proposed framework; and (iv) the perturbation process is accomplished by the alteration of the original attribute value by a new value (clusters centroid). The effectiveness of the proposed PPFSCADA framework is shown through several experiments on simulated SCADA, intrusion detection and network traffic data sets. Through experimental analysis, we show that PPFSCADA effectively deals with multivariate traffic attributes, producing compatible results as the original data, and also substantially improving the performance of the five supervised approaches and provides high level of privacy protection. © 2014 Published by Elsevier B.V. All rights reserved.

Inference in differences-in-differences with few treated groups and heteroskedasticity

Differences-in-Differences (DID) is one of the most widely used identification strategies in applied economics. However, how to draw inferences in DID models when there are few treated groups remains an open question. We show that the usual inference methods used in DID models might not perform well when there are few treated groups and errors are heteroskedastic. In particular, we show that when there is variation in the number of observations per group, inference methods designed to work when there are few treated groups tend to (under-) over-reject the null hypothesis when the treated groups are (large) small relative to the control groups. This happens because larger groups tend to have lower variance, generating heteroskedasticity in the group x time aggregate DID model. We provide evidence from Monte Carlo simulations and from placebo DID regressions with the American Community Survey (ACS) and the Current Population Survey (CPS) datasets to show that this problem is relevant even in datasets with large numbers of observations per group. We then derive an alternative inference method that provides accurate hypothesis testing in situations where there are few treated groups (or even just one) and many control groups in the presence of heteroskedasticity. Our method assumes that we can model the heteroskedasticity of a linear combination of the errors. We show that this assumption can be satisfied without imposing strong assumptions on the errors in common DID applications. With many pre-treatment periods, we show that this assumption can be relaxed. Instead, we provide an alternative inference method that relies on strict stationarity and ergodicity of the time series. Finally, we consider two recent alternatives to DID when there are many pre-treatment periods. We extend our inference methods to linear factor models when there are few treated groups. We also derive conditions under which a permutation test for the synthetic control estimator proposed by Abadie et al. (2010) is robust to heteroskedasticity and propose a modification on the test statistic that provided a better heteroskedasticity correction in our simulations.

Inference in differences-in-differences with few treated groups and heteroskedasticity

Differences-in-Differences (DID) is one of the most widely used identification strategies in applied economics. However, how to draw inferences in DID models when there are few treated groups remains an open question. We show that the usual inference methods used in DID models might not perform well when there are few treated groups and errors are heteroskedastic. In particular, we show that when there is variation in the number of observations per group, inference methods designed to work when there are few treated groups tend to (under-) over-reject the null hypothesis when the treated groups are (large) small relative to the control groups. This happens because larger groups tend to have lower variance, generating heteroskedasticity in the group x time aggregate DID model. We provide evidence from Monte Carlo simulations and from placebo DID regressions with the American Community Survey (ACS) and the Current Population Survey (CPS) datasets to show that this problem is relevant even in datasets with large numbers of observations per group. We then derive an alternative inference method that provides accurate hypothesis testing in situations where there are few treated groups (or even just one) and many control groups in the presence of heteroskedasticity. Our method assumes that we know how the heteroskedasticity is generated, which is the case when it is generated by variation in the number of observations per group. With many pre-treatment periods, we show that this assumption can be relaxed. Instead, we provide an alternative application of our method that relies on assumptions about stationarity and convergence of the moments of the time series. Finally, we consider two recent alternatives to DID when there are many pre-treatment groups. We extend our inference method to linear factor models when there are few treated groups. We also propose a permutation test for the synthetic control estimator that provided a better heteroskedasticity correction in our simulations than the test suggested by Abadie et al. (2010).

The use of nonparametric contrasts in one-way layouts and random block designs

Nonparametric simple-contrast estimates for one-way layouts based on Hodges-Lehmann estimators for two samples and confidence intervals for all contrasts involving only two treatments are found in the literature.Tests for such contrasts are performed from the distribution of the maximum of the rank sum between two treatments. For random block designs, simple contrast estimates based on Hodges-Lehmann estimators for one sample are presented. However, discussions concerning the significance levels of more complex contrast tests in nonparametric statistics are not well outlined.This work aims at presenting a methodology to obtain p-values for any contrast types based on the construction of the permutations required by each design model using a C-language program for each design type. For small samples, all possible treatment configurations are performed in order to obtain the desired p-value. For large samples, a fixed number of random configurations are used. The program prompts the input of contrast coefficients, but does not assume the existence or orthogonality among them.In orthogonal contrasts, the decomposition of the value of the suitable statistic for each case is performed and it is observed that the same procedure used in the parametric analysis of variance can be applied in the nonparametric case, that is, each of the orthogonal contrasts has a chi(2) distribution with one degree of freedom. Also, the similarities between the p-values obtained for nonparametric contrasts and those obtained through approximations suggested in the literature are discussed.

Morphometric analysis of treatment effects of the Balters bionator in growing Class II patients

Objective: To investigate the effects of the standard (Class II) Balters bionator in growing patients with Class II malocclusion with mandibular retrusion by using morphometrics (thin-plate spline [TPS] analysis). Materials and Methods: Thirty-one Class II patients (17 male and 14 female) were treated with the Balters bionator (bionator group). Mean age at the start of treatment (T0) was 10.3 years, while it was 13 years at the end of treatment (T1). Mean treatment time was 2 years and 2 months. The control group consisted of 22 subjects (14 male and 8 female) with untreated Class II malocclusion. Mean age at T0 was 10.2 years, while it was 12.2 years at T1. The observation period lasted 2 years on average. TPS analysis evaluated statistical (permutation tests) differences in the craniofacial shape and size between the bionator and control groups. Results: Through TPS analysis (deformation grids) the bionator group showed significant shape changes in the mandible that could be described as a mandibular forward and downward displacement. The control group showed no statistically significant differences in the correction of Class II malocclusion. Conclusions: Bionator appliance is able to induce significant mandibular shape changes that lead to the correction of Class II dentoskeletal disharmony. © 2013 by The EH Angle Education and Research Foundation, Inc.