A REAPPRAISAL OF GENERIC AND SUBGENERIC CLASSIFICATION IN THE BATRACHOSPERMACEAE (RHODOPHYTA)

The generic and subgeneric classification of the family Batrachospermaceae (Rhodophyta) has long been recognized as ambiguous and often inconsistent. One of the prime features used to delineate sections of Batrachospermum, trichogyne shape, is variable even within given species. However, characters associated with the carposporophyte and the carpogonial branch, as well as carpogonial symmetry, are practical and consistent taxonomic criteria. These features have been used to redefine sectional delineation in Batrachospermum. Based on phylogenetic reasoning and practicality, it is proposed that the three genera Nothocladus, Sirodotia and Tuomeya be reduced to sectional level within Batrachospermum. The genus Batrachospermum would thus become the sole member of the Batrachospermaceae and would include two subgenera, Batrachospermum and Acarposporophytum, the former with nine clearly defined sections (Aristata, Batrachospermum, Contorta, Hybrida, Nothocladus (Skuja) stat. nov., Sirodotia (Kylin) stat. nov., Tuomeya (Harvey) stat. nov., Turficola and Viridia). As a result, the following nomenclatural changes are proposed: Batrachospermum lindaueri (Skuja) comb. nov., B. nodosum (Skuja) comb. nov., B. delicatulum (Skuja) comb. nov., B. fennicum (Skuja) comb. nov., B. suecicum (Kylin) comb. nov. and B. americanum (Kutzing) comb. nov.

The Mexican maquila industry and the environment: an overview of the issues

Includes bibliography

Computer techniques towards the automatic characterization of graphite particles in metallographic images of industrial materials

The automatic characterization of particles in metallographic images has been paramount, mainly because of the importance of quantifying such microstructures in order to assess the mechanical properties of materials common used in industry. This automated characterization may avoid problems related with fatigue and possible measurement errors. In this paper, computer techniques are used and assessed towards the accomplishment of this crucial industrial goal in an efficient and robust manner. Hence, the use of the most actively pursued machine learning classification techniques. In particularity, Support Vector Machine, Bayesian and Optimum-Path Forest based classifiers, and also the Otsu's method, which is commonly used in computer imaging to binarize automatically simply images and used here to demonstrated the need for more complex methods, are evaluated in the characterization of graphite particles in metallographic images. The statistical based analysis performed confirmed that these computer techniques are efficient solutions to accomplish the aimed characterization. Additionally, the Optimum-Path Forest based classifier demonstrated an overall superior performance, both in terms of accuracy and speed. © 2012 Elsevier Ltd. All rights reserved.

A new approach to soil classification mapping based on the spatial distribution of soil properties

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Classificação morfológica e imunostoquímica em microarranjo de tecido (TMA) de linfomas não-Hodgkin em cães conforme os critérios da Histological Classification od Hematopoietic Tumors of Domestic Animals (WHO)

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Estimation of croplands using indicator kriging and fuzzy classification

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Developing a classification system of social communication functioning of preschool children with autism spectrum disorder

Background: Impairments in social communication are the hallmark feature of autism spectrum disorder (ASD). Operationalizing ‘severity’ in ASD has been challenging; thus stratifying by functioning has not been possible. Purpose: To describe the development of the Autism Classification System of Functioning: Social Communication (ACSF:SC) and evaluate its consistency within and between parent and professional ratings. Methodology: (1)ACSF:SC development based on focus groups and surveys involving parents, educators and clinicians familiar with preschoolers with ASD; and (2)Evaluation of the intra- and inter-rater agreement of the ACSF:SC using weighted kappa(кw). Results: Seventy-six participants were involved in the development process. Core characteristics of social communication were ascertained: communicative intent; communicative skills and reciprocity; and impact of environment. Five ACSF:SC levels were created and content-validated across participants. Best capacity and typical performance agreement ratings varied as follows: intra-rater on 41 children was кw=0.61-0.69 for parents and кw=0.71-0.95 for professionals; inter-rater between professionals were кw=0.47-0.61 and between parents and professionals кw=0.33-0.53. Conclusions: Perspectives from parents, and professionals informed ACSF:SC development, providing common descriptions of the levels of everyday communicative abilities of children with ASD to complement DSM-5. Rater agreement demonstrates the ACSF:SC can be utilized with acceptable consistency in comparison to other functional classification systems.

Automatic solder joint defect classification using the Log-Gabor filter

This paper proposes the validity of a Gabor filter bank for feature extraction of solder joint images on Printed Circuit Boards (PCBs). A distance measure based on the Mahalanobis Cosine metric is also presented for classification of five different types of solder joints. From the experimental results, this methodology achieved high accuracy and a well generalised performance. This can be an effective method to reduce cost and improve quality in the production of PCBs in the manufacturing industry.

A new approach for finding an appropriate combination of texture parameters for classification

This paper suggests an approach for finding an appropriate combination of various parameters for extracting texture features (e.g. choice of spectral band for extracting texture feature, size of the moving window, quantization level of the image, and choice of texture feature etc.) to be used in the classification process. Gray level co-occurrence matrix (GLCM) method has been used for extracting texture from remotely sensed satellite image. Results of the classification of an Indian urban environment using spatial property (texture), derived from spectral and multi-resolution wavelet decomposed images have also been reported. A multivariate data analysis technique called ‘conjoint analysis’ has been used in the study to analyze the relative importance of these parameters. Results indicate that the choice of texture feature and window size have higher relative importance in the classification process than quantization level or the choice of image band for extracting texture feature. In case of texture features derived using wavelet decomposed image, the parameter ‘decomposition level’ has almost equal relative importance as the size of moving window and the decomposition of images up to level one is sufficient and there is no need to go for further decomposition. It was also observed that the classification incorporating texture features improves the overall classification accuracy in a statistically significant manner in comparison to pure spectral classification.

Were regulatory changes in reporting "abnormal items" justified? : evidence of intra-period classificatory earnings management practices in Australia

Purpose Managers generally have discretion in determining how components of earnings are presented in financial statements in distinguishing between ‘normal’ earnings and items classified as unusual, special, significant, exceptional or abnormal. Prior research has found that such intra-period classificatory choice is used as a form of earnings management. Prior to 2001, Australian accounting standards mandated that unusually large items of revenue and expense be classified as ‘abnormal items’ for financial reporting, but this classification was removed from accounting standards from 2001. This move by the regulators was partly in response to concerns that the abnormal classification was being used opportunistically to manage reported pre-abnormal earnings. This study extends the earnings management literature by examining the reporting of abnormal items for evidence of intra-period classificatory earnings management in the unique Australian setting. Design/methodology/approach This study investigates associations between reporting of abnormal items and incentives in the form of analyst following and the earnings benchmarks of analysts’ forecasts, earnings levels, and earnings changes, for a sample of Australian top-500 firms for the seven-year period from 1994 to 2000. Findings The findings suggest there are systematic differences between firms reporting abnormal items and those with no abnormal items. Results show evidence that, on average, firms shifted expense items from pre-abnormal earnings to bottom line net income through reclassification as abnormal losses. Originality/value These findings suggest that the standard setters were justified in removing the ‘abnormal’ classification from the accounting standard. However, it cannot be assumed that all firms acted opportunistically in the classification of items as abnormal. With the removal of the standardised classification of items outside normal operations as ‘abnormal’, firms lost the opportunity to use such disclosures as a signalling device, with the consequential effect of limiting the scope of effectively communicating information about the nature of items presented in financial reports.

Structure matters: Adoption of structured classification Approach in the context of cognitive presence classification

Within online learning communities, receiving timely and meaningful insights into the quality of learning activities is an important part of an effective educational experience. Commonly adopted methods – such as the Community of Inquiry framework – rely on manual coding of online discussion transcripts, which is a costly and time consuming process. There are several efforts underway to enable the automated classification of online discussion messages using supervised machine learning, which would enable the real-time analysis of interactions occurring within online learning communities. This paper investigates the importance of incorporating features that utilise the structure of on-line discussions for the classification of "cognitive presence" – the central dimension of the Community of Inquiry framework focusing on the quality of students' critical thinking within online learning communities. We implemented a Conditional Random Field classification solution, which incorporates structural features that may be useful in increasing classification performance over other implementations. Our approach leads to an improvement in classification accuracy of 5.8% over current existing techniques when tested on the same dataset, with a precision and recall of 0.630 and 0.504 respectively.

Vermicular graphite cast iron current state of the art

Vermicular graphite cast iron is a new addition to the family of cast irons. Various methods for producing vermicular graphite cast iron are briefly discussed in this paper. The mechanical and physical properties of cast irons with vermicular graphite have been found to be intermediate between those of gray and ductile irons. Other properties such as casting characteristics, scaling resistance, damping capacity and machinability have been compared with those of gray and ductile irons. Probable applications of vermicular graphite cast irons are suggested.

Problems of Proto-Slavic Historical Nominal Morphology : On the Basis of Old Church Slavic

In this study I offer a diachronic solution for a number of difficult inflectional endings in Old Church Slavic nominal declensions. In this context I address the perhaps most disputed and the most important question of the Slavic nominal inflectional morphology: whether there was in Proto-Slavic an Auslautgesetz (ALG), a law of final syllables, that narrowed the Proto-Indo-European vowel */o/ to */u/ in closed word-final syllables. In addition, the work contains an exhaustive morphological classification of the nouns and adjectives that occur in canonical Old Church Slavic. I argue that Proto-Indo-European */o/ became Proto-Slavic */u/ before word-final */s/ and */N/. This conclusion is based on the impossibility of finding credible analogical (as opposed to phonological) explanations for the forms supporting the ALG hypothesis, and on the survival of the neuter gender in Slavic. It is not likely that the */o/-stem nominative singular ending */-u/ was borrowed from the accusative singular, because the latter would have been the only paradigmatic form with the stem vowel */-u-/. It is equally unlikely that the ending */-u/ was borrowed from the */u/-stems, because the latter constituted a moribund class. The usually stated motivation for such an analogical borrowing, i.e. a need to prevent the merger of */o/-stem masculines with neuters of the same class, is not tenable. Extra-Slavic, as well as intra-Slavic evidence suggests that phonologically-triggered mergers between two semantically opaque genders do not tend to be prevented, but rather that such mergers lead to the loss of the gender opposition in question. On the other hand, if */-os/ had not become */-us/, most nouns and, most importantly, all adjectives and pronouns would have lost the formal distinction between masculines and neuters. This would have necessarily resulted in the loss of the neuter gender. A new explanation is given for the most apparent piece of evidence against the ALG hypothesis, the nominative-accusative singular of the */es/-stem neuters, e.g. nebo 'sky'. I argue that it arose in late Proto-Slavic dialects, replacing regular nebe, under the influence of the */o/- and */yo/-stems where a correlation had emerged between a hard root-final consonant and the termination -o, on the one hand, and a soft root-final consonant and the termination -e, on the other.

Theory and Analysis of Classic Heavy Metal Harmony

This thesis explores melodic and harmonic features of heavy metal, and while doing so, explores various methods of music analysis; their applicability and limitations regarding the study of heavy metal music. The study is built on three general hypotheses according to which 1) acoustic characteristics play a significant role for chord constructing in heavy metal, 2) heavy metal has strong ties and similarities with other Western musical styles, and 3) theories and analytical methods of Western art music may be applied to heavy metal. It seems evident that in heavy metal some chord structures appear far more frequently than others. It is suggested here that the fundamental reason for this is the use of guitar distortion effect. Subsequently, theories as to how and under what principles heavy metal is constructed need to be put under discussion; analytical models regarding the classification of consonance and dissonance and chord categorization are here revised to meet the common practices of this music. It is evident that heavy metal is not an isolated style of music; it is seen here as a cultural fusion of various musical styles. Moreover, it is suggested that the theoretical background to the construction of Western music and its analysis can offer invaluable insights to heavy metal. However, the analytical methods need to be reformed to some extent to meet the characteristics of the music. This reformation includes an accommodation of linear and functional theories that has been found rather rarely in music theory and musicology.

Site classification and estimation of surface level seismic hazard using geophysical data and probabilistic approach

This paper presents the site classification of Bangalore Mahanagar Palike (BMP) area using geophysical data and the evaluation of spectral acceleration at ground level using probabilistic approach. Site classification has been carried out using experimental data from the shallow geophysical method of Multichannel Analysis of Surface wave (MASW). One-dimensional (1-D) MASW survey has been carried out at 58 locations and respective velocity profiles are obtained. The average shear wave velocity for 30 m depth (Vs(30)) has been calculated and is used for the site classification of the BMP area as per NEHRP (National Earthquake Hazards Reduction Program). Based on the Vs(30) values major part of the BMP area can be classified as ``site class D'', and ``site class C'. A smaller portion of the study area, in and around Lalbagh Park, is classified as ``site class B''. Further, probabilistic seismic hazard analysis has been carried out to map the seismic hazard in terms spectral acceleration (S-a) at rock and the ground level considering the site classes and six seismogenic sources identified. The mean annual rate of exceedance and cumulative probability hazard curve for S. have been generated. The quantified hazard values in terms of spectral acceleration for short period and long period are mapped for rock, site class C and D with 10% probability of exceedance in 50 years on a grid size of 0.5 km. In addition to this, the Uniform Hazard Response Spectrum (UHRS) at surface level has been developed for the 5% damping and 10% probability of exceedance in 50 years for rock, site class C and D These spectral acceleration and uniform hazard spectrums can be used to assess the design force for important structures and also to develop the design spectrum.