Mapping the knowledge covered by library classification systems

This study explores, in 3 steps, how the 3 main library classification systems, the Library of Congress Classification, the Dewey Decimal Classification, and the Universal Decimal Classification, cover human knowledge. First, we mapped the knowledge covered by the 3 systems. We used the 10 Pillars of Knowledge: Map of Human Knowledge, which comprises 10 pillars, as an evaluative model. We mapped all the subject-based classes and subclasses that are part of the first 2 levels of the 3 hierarchical structures. Then, we zoomed into each of the 10 pillars and analyzed how the three systems cover the 10 knowledge domains. Finally, we focused on the 3 library systems. Based on the way each one of them covers the 10 knowledge domains, it is evident that they failed to adequately and systematically present contemporary human knowledge. They are unsystematic and biased, and, at the top 2 levels of the hierarchical structures, they are incomplete.

Submucous fibroids classification - STEP-W classification

Objective: To develop a new submucous fibroids classification for evaluating the viability and the degree of difficulty and complexity of a hysteroscopic myomectomy.Methods: We have included more four parameters in addition to penetration the fibroid into the myometrium. The extra-parameters were: size of the fibroid, it topography, it extension of the base in relation the wall was set and the wall it was set. The fibroids were classified according to the Classification of the European Society for Gynaecological Endoscopy (ESGE) and to the new classification (STEP-W) in patients who were submitted to hysteroscopic resection of submucous fibroids. The possibility of total resection of the fibroid, the operating time, the fluid deficit and the frequency of any complications were considered. The Fisher test, the Student t test and the analysis of variance test were used in the statistical analyses. It was considered statistically significant when the p-value was less than 0.05 in the two-tailed test.Results: In group which the hysteroscopic surgery was considered complete there was no significant difference between the three ESGE levels (0, 1 and 2). Using the STEP-W, the difference between the numbers of complete surgeries was significant (p < 0.001) for the two levels (groups I and II). The difference between the operating times was significant for the two classifications. In relation to the fluid deficit, only the STEP-W showed significant differences between the levels (p=0.02).Conclusions: It seems to us that the new classification (STEP-W) gives more clues to the difficulties of a hysteroscopic myornectomy than the standard classification (ESGE).

Multi-method Study on Aquatic Humic Substances from the Rio Negro - Amazonas State/Brazil: Emphasis on Molecular-Size Classification of their Metal Contents

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

Submucous myomas: A new presurgical classification to evaluate the viability of hysteroscopic surgical treatment - Preliminary report

STUDY OBJECTIVE: To develop a new preoperative classification of submucous myomas for evaluating the viability and the degree of difficulty of hysteroscopic myomectomy.DESIGN: Retrospective study (Canadian Task Force classification II-3)SETTING: University teaching hospitals.PATIENTS: Fifty-five patients who underwent hysteroscopic resection of submucous myomas.INTERVENTION: the possibility of total resection of the myoma, the operating time, the fluid deficit, and the frequency of any complications were considered. The myomas were classified according to the Classification of the European Society for Gynaecological Endoscopy (ESGE) and by our group's new classification (NC), which considers not only the degree of penetration of the myoma into the myometrium, but also adds in such parameters as the distance of the base of the myoma from the uterine wall, the size of the nodule (cm), and the topography of the uterine cavity. The Fisher's exact test, the Student's t test, and the analysis of variance test were used in the statistical analysis. A p value less than .05 in the two-tailed test was considered significant.MEASUREMENTS AND MAIN RESULTS: In 57 myomas, hysteroscopic surgery was considered complete. There was no significant difference among the three ESGE levels (0, 1, and 2). Using the NC, the difference between the numbers of complete surgeries was significant (p < .001) for the two levels (groups I and H). The difference between the operating times was significant for the two classifications. With respect to the fluid deficit, only the NC showed significant differences between the levels (p = .02).CONCLUSIONS: We believe that the NC gives more clues as to the difficulties of a hysteroscopic myomectomy than the standard ESGE classification. It should be stressed that the number of hysteroscopic myomectomies used in this analysis was low, and it would be interesting to evaluate the performance of the classification in a larger number of patients. (c) 2005 AAGL. All rights reserved.

Malware distributed collection and pre-classification system using honeypot technology

Malware has become a major threat in the last years due to the ease of spread through the Internet. Malware detection has become difficult with the use of compression, polymorphic methods and techniques to detect and disable security software. Those and other obfuscation techniques pose a problem for detection and classification schemes that analyze malware behavior. In this paper we propose a distributed architecture to improve malware collection using different honeypot technologies to increase the variety of malware collected. We also present a daemon tool developed to grab malware distributed through spam and a pre-classification technique that uses antivirus technology to separate malware in generic classes. © 2009 SPIE.

New trends in musical genre classification using optimum-path forest

Musical genre classification has been paramount in the last years, mainly in large multimedia datasets, in which new songs and genres can be added at every moment by anyone. In this context, we have seen the growing of musical recommendation systems, which can improve the benefits for several applications, such as social networks and collective musical libraries. In this work, we have introduced a recent machine learning technique named Optimum-Path Forest (OPF) for musical genre classification, which has been demonstrated to be similar to the state-of-the-art pattern recognition techniques, but much faster for some applications. Experiments in two public datasets were conducted against Support Vector Machines and a Bayesian classifier to show the validity of our work. In addition, we have executed an experiment using very recent hybrid feature selection techniques based on OPF to speed up feature extraction process. © 2011 International Society for Music Information Retrieval.

Automatic classification of fish germ cells through optimum-path forest

The spermatogenesis is crucial to the species reproduction, and its monitoring may shed light over some important information of such process. Thus, the germ cells quantification can provide useful tools to improve the reproduction cycle. In this paper, we present the first work that address this problem in fishes with machine learning techniques. We show here how to obtain high recognition accuracies in order to identify fish germ cells with several state-of-the-art supervised pattern recognition techniques. © 2011 IEEE.